Inferring age mixing from transmission clusters: Missing at Random (women = 70%)
David Niyukuri
Sunday 12 January 2020
Inferring age mixing from transmission clusters in a data missingess of Missing Completly at Random. This means during sampling, a missing individual is considered to be missing randomly (without any explanation or cause).
suppressMessages(library(dplyr))
suppressMessages(library(ggplot2))
suppressMessages(library(kableExtra))# Function to summarised outputs
# library(gmodels) # no more use of ci()
quant.med <- function(input){
input <- na.omit(input)
quantirles.v <- quantile(input, probs = seq(0, 1, 0.25))
quantirles.25.50.75 <- as.numeric(quantirles.v)[2:4]
return(quantirles.25.50.75)
}
min.max.sd.mean <- function(input){
input <- na.omit(input)
min.v <- min(input)
max.v <- max(input)
mean.v <- mean(input)
sd.v <- sd(input)
min.max.sd.mean.v <- c(min.v, max.v, mean.v, sd.v)
return(min.max.sd.mean.v)
}
# Function for Average Root Mean Squared Error
ARMSE <- function(v1=v1, v2=v2) {
d <- data.frame(v1,v2)
r <- na.omit(d)
y1 <- r[,1]
y2 <- r[,2]
error.na <- (y1-y2)/y2
armse <- sqrt(mean(error.na^2))
return(armse)}
# Function for Root Mean Squared Error
RMSE <- function(error) {
error <- as.numeric(na.omit(error))
rmse <- sqrt(mean(error^2))
return(rmse)}
# Function for Mean Absolute Error
MAE <- function(error) {
error <- as.numeric(na.omit(error))
mae <- mean(abs(error))
return(mae)
}
# Function for Mean Realative Error
MRE <- function(error) {
error <- as.numeric(na.omit(error))
mae <- mean(error)
return(mae)
}
# set_names(c("Centre", "Conforme", "Ne conforme pas", "Total admis", "% conforme")) %>%
# flextable::flextable() %>%
# flextable::autofit()# dr2 <- read.csv("/home/david/age_mixing_patterns_phylogenetic/sim_outputs/F_results.mcarmar.large.AD_280_new_params_111.csv")
# dr3 <- read.csv("/home/david/age_mixing_patterns_phylogenetic/sim_outputs/F_results.mcarmar.large.AD_280_new_params_444.csv")
# dr4 <- read.csv("/home/david/age_mixing_patterns_phylogenetic/sim_outputs/F_results.mcarmar.large.AD_280_new_params_888.csv")
# dr1 <- read.csv("/home/david/age_mixing_patterns_phylogenetic/sim_outputs/F_results.mcarmar.large.AD_280_new_params_111777.csv")
# dr <- rbind(dr1, dr2, dr3, dr4)
# write.csv(dr, file = "/home/david/age_mixing_patterns_phylogenetic/sim_outputs/F_results.mcarmar.large.AD.csv")
dr <- read.csv("/home/david/age_mixing_patterns_phylogenetic/sim_outputs/F_results.mcarmar.large.AD.csv")1 Epidemic characteristics
An HIV epidemic was simulated in an age and gender structured population. With an initial population of 10000 men and 10000 women, the simulation time was 40 years, and the infection was introduced in the population at the 10th year among randomly selected 10 individuals within 20 and 50 of age range. During simulation, demographic events like birth, and death were considered together with sexual partnerships. Refering to real world history of HIV, mainly ART treatment, we gradually allow interventions based on CD4 counts. With a seed sequence sampled in 1989, we assume it existed two years before (1987). It means that the simulation of started in 1977, and the infection was introduced in 1987 for 30 years in 2017. With same parameter combination, we performed 1120 simulations, and the statistics presented below will be minimum, median, mean, and maximum values of all 1120 simulations.
params <- c("formation.hazard.agegapry.baseline",
"person.agegap.man.dist.normal.mu",
"person.agegap.woman.dist.normal.mu",
"person.agegap.man.dist.normal.sigma",
"person.agegap.woman.dist.normal.sigma")
vals <- c(2 , 10, 10, 5, 5)
description <- c("baseline value of age difference
between a man and woman in relationship",
"mean of preferred age differences
distribution for men",
"mean of preferred age differences
distribution for women",
"standard deviation of preferred age
differences distribution for men",
"standard deviation of preferred age
differences distribution for women")
params.setup <- data.frame(params, vals, description)
colnames(params.setup) <- c("parameter associated to age mixing", "value", "description")
params.setup %>%
kable() %>%
kable_styling("striped") | parameter associated to age mixing | value | description |
|---|---|---|
| formation.hazard.agegapry.baseline | 2 | baseline value of age difference between a man and woman in relationship |
| person.agegap.man.dist.normal.mu | 10 | mean of preferred age differences distribution for men |
| person.agegap.woman.dist.normal.mu | 10 | mean of preferred age differences distribution for women |
| person.agegap.man.dist.normal.sigma | 5 | standard deviation of preferred age differences distribution for men |
| person.agegap.woman.dist.normal.sigma | 5 | standard deviation of preferred age differences distribution for women |
write.csv(params.setup, file = "/home/david/age_mixing_patterns_phylogenetic/results/MAR_a/Table_a_1_Model_Parameters.csv")If we consider time point sampling at 40 simulation time, we can see that the epidemic is characterized by an increasing prevalence across early age groups in both men and women, with women carrying the most of the burden. After 40 years the trend reversed with a high prevalence among men and the lowest among women. The simulated epidemic looks like a typical sub-Saharan Africa epidemic.
1.1 Prevalence
The following table and figure show values of point prevalence at 40 simulation time among different age groups.
hiv.prev <- dr %>%
select(starts_with("prev."))
prev.m.15.24 <- quant.med(hiv.prev$prev.m.15.24)
prev.m.25.29 <- quant.med(hiv.prev$prev.m.25.29)
prev.m.30.34 <- quant.med(hiv.prev$prev.m.30.34)
prev.m.35.39 <- quant.med(hiv.prev$prev.m.35.39)
prev.m.40.44 <- quant.med(hiv.prev$prev.m.40.44)
prev.m.45.49 <- quant.med(hiv.prev$prev.m.45.49)
prev.w.15.24 <- quant.med(hiv.prev$prev.w.15.24)
prev.w.25.29 <- quant.med(hiv.prev$prev.w.25.29)
prev.w.30.34 <- quant.med(hiv.prev$prev.w.30.34)
prev.w.35.39 <- quant.med(hiv.prev$prev.w.35.39)
prev.w.40.44 <- quant.med(hiv.prev$prev.w.40.44)
prev.w.45.49 <- quant.med(hiv.prev$prev.w.45.49)
val.prev.F <- c(prev.m.15.24[2], prev.m.25.29[2], prev.m.30.34[2], prev.m.35.39[2], prev.m.40.44[2], prev.m.45.49[2],
prev.w.15.24[2], prev.w.25.29[2], prev.w.30.34[2], prev.w.35.39[2], prev.w.40.44[2], prev.w.45.49[2])
val.prev.L <- c(prev.m.15.24[1], prev.m.25.29[1], prev.m.30.34[1], prev.m.35.39[1], prev.m.40.44[1], prev.m.45.49[1],
prev.w.15.24[1], prev.w.25.29[1], prev.w.30.34[1], prev.w.35.39[1], prev.w.40.44[1], prev.w.45.49[1])
val.prev.U <- c(prev.m.15.24[3], prev.m.25.29[3], prev.m.30.34[3], prev.m.35.39[3], prev.m.40.44[3], prev.m.45.49[3],
prev.w.15.24[3], prev.w.25.29[3], prev.w.30.34[3], prev.w.35.39[3], prev.w.40.44[3], prev.w.45.49[3])
par.gender <- c(rep("Men", 6), rep("Women", 6))
agegroup <- rep(c("15-24", "25-29", "30-34", "35-39", "40-44", "45-49"), 2)
val.prev <- data.frame(agegroup, val.prev.L, val.prev.F, val.prev.U, par.gender)
val.prev.tab <- val.prev
names(val.prev.tab) <- c("age_group", "lower.Q1", "median", "upper.Q3", "gender")
val.prev.tab %>%
kable() %>%
kable_styling("striped") | age_group | lower.Q1 | median | upper.Q3 | gender |
|---|---|---|---|---|
| 15-24 | 0.0096192 | 0.0135247 | 0.0178232 | Men |
| 25-29 | 0.0321657 | 0.0402010 | 0.0497982 | Men |
| 30-34 | 0.0558920 | 0.0665703 | 0.0785671 | Men |
| 35-39 | 0.0698925 | 0.0858586 | 0.1019193 | Men |
| 40-44 | 0.0816493 | 0.0920245 | 0.1022722 | Men |
| 45-49 | 0.0716988 | 0.0807847 | 0.0907243 | Men |
| 15-24 | 0.0576923 | 0.0670897 | 0.0774699 | Women |
| 25-29 | 0.0952381 | 0.1079414 | 0.1227154 | Women |
| 30-34 | 0.1037026 | 0.1176434 | 0.1363636 | Women |
| 35-39 | 0.0853812 | 0.1040033 | 0.1269454 | Women |
| 40-44 | 0.0514376 | 0.0626058 | 0.0769911 | Women |
| 45-49 | 0.0407332 | 0.0510384 | 0.0632753 | Women |
write.csv(val.prev.tab, file = "/home/david/age_mixing_patterns_phylogenetic/results/MAR_a/Table_a_2_Prevalence.csv")val.prev <- data.frame(agegroup, val.prev.L, val.prev.F, val.prev.U, par.gender)
names(val.prev) <- c("age_group", "lower.Q1", "median", "upper.Q3", "Gender")
plot.prev.men.women <- ggplot(val.prev, aes(x=age_group, y=median, colour=Gender, group = Gender)) +
geom_errorbar(aes(ymin=lower.Q1, ymax=upper.Q3), width=.1) +
geom_line(size=.3) +
geom_point() +
xlab("Age Groups") + ylab("HIV prevalence")
print(plot.prev.men.women)
ggsave(filename = "Plot_a_1_Prevalence.pdf",
plot = plot.prev.men.women,
path = "/home/david/age_mixing_patterns_phylogenetic/results/MAR_a",
width = 16, height = 10, units = "cm")1.2 Incidence
The age mixing in partnership and transmission will be studied within a time interval of 35 - 40 years of running time. The incidence among three age groups per gender is shown by the following figure. We can see that younger women had a lot of new cases compared to men in same age group, but men within 25 - 39, and 40 - 49 have much cases compared to women of same age groups.
hiv.inc <- dr %>%
select(starts_with("R.inc."))
inc.15.25.m <- quant.med(hiv.inc$R.inc.15.25.m)
inc.25.40.m <- quant.med(hiv.inc$R.inc.25.40.m)
inc.40.50.m <- quant.med(hiv.inc$R.inc.40.50.m)
inc.15.25.w <- quant.med(hiv.inc$R.inc.15.25.w)
inc.25.40.w <- quant.med(hiv.inc$R.inc.25.40.w)
inc.40.50.w <- quant.med(hiv.inc$R.inc.40.50.w)
Gender <- c(rep("Men", 3), rep("Women", 3))
age_group <- rep(c("15-24", "25-39", "40-49"), 2)
val.inc.F <- c(inc.15.25.m[2], inc.25.40.m[2], inc.40.50.m[2],
inc.15.25.w[2], inc.25.40.w[2], inc.40.50.w[2])
val.inc.L <- c(inc.15.25.m[1], inc.25.40.m[1], inc.40.50.m[1],
inc.15.25.w[1], inc.25.40.w[1], inc.40.50.w[1])
val.inc.U <- c(inc.15.25.m[3], inc.25.40.m[3], inc.40.50.m[3],
inc.15.25.w[3], inc.25.40.w[3], inc.40.50.w[3])
val.inc <- data.frame(val.inc.L, val.inc.F, val.inc.U, Gender, age_group)
table.val.inc <- data.frame(age_group, val.inc.L, val.inc.F, val.inc.U, Gender)
names(table.val.inc) <- c("age_group", "lower.Q1", "median", "upper.Q3", "Gender")
table.val.inc %>%
kable() %>%
kable_styling("striped")| age_group | lower.Q1 | median | upper.Q3 | Gender |
|---|---|---|---|---|
| 15-24 | 0.0020863 | 0.0028811 | 0.0039290 | Men |
| 25-39 | 0.0042933 | 0.0056458 | 0.0069273 | Men |
| 40-49 | 0.0015097 | 0.0019660 | 0.0025154 | Men |
| 15-24 | 0.0077611 | 0.0091388 | 0.0109045 | Women |
| 25-39 | 0.0004071 | 0.0006323 | 0.0009208 | Women |
| 40-49 | 0.0000000 | 0.0000000 | 0.0001357 | Women |
write.csv(table.val.inc, file = "/home/david/age_mixing_patterns_phylogenetic/results/MAR_a/Table_a_3_Incidence.csv")plot.inc.men.women <- ggplot(val.inc, aes(x=age_group, y=val.inc.F, colour=Gender, group = Gender)) +
geom_errorbar(aes(ymin=val.inc.L, ymax=val.inc.U), width=.1) +
geom_line(size=.3) +
geom_point() +
xlab("Age Groups") + ylab("HIV incidence")
print(plot.inc.men.women)
ggsave(filename = "Plot_a_2_Incidence.pdf",
plot = plot.inc.men.women,
path = "/home/david/age_mixing_patterns_phylogenetic/results/MAR_a",
width = 16, height = 10, units = "cm")1.3 Sexual behaviour
In this simulation study, sexual behaviour of interest were mainly based on number of sexual partners and age preference which is reflected from age difference between sexual partners.
1.3.1 Point prevalence of concurrent partnerships
When we consider past 6 months (1/2) from simulation time 40, the point prevalence of concurrent partnership is:
prev.conc.p <- dr %>%
select(starts_with("R.p.prev."))
prev.conc.p.val <- quant.med(prev.conc.p$R.p.prev.6months.m)
prev.conc.p.val <- c(prev.conc.p.val[1], prev.conc.p.val[2], prev.conc.p.val[3])
names(prev.conc.p.val) <- c("lower.Q1", "med", "upper.Q3")
prev.conc.p.val %>%
kable() %>%
kable_styling("striped") | x | |
|---|---|
| lower.Q1 | 0.0157392 |
| med | 0.0167542 |
| upper.Q3 | 0.0177862 |
write.csv(prev.conc.p.val, file = "/home/david/age_mixing_patterns_phylogenetic/results/MAR_a/Table_a_4_Prevalence_Concurrency.csv")1.3.2 Age mixing in partnership
Age mixing patterns is defined as population-level patterns for how people choose partners with regards to age. If we consider past 5 years from simulation time 40, we have the following statistics of age mixing patterns in partnership.
1.3.2.1 True population level age mixing patterns in overall partnerships
In the fllowing analysis we depict popultion level age mixing patterns by computing different statistics based on age difference between man age and woman age.
- AAD: average age difference across all relationships
- VAD: variance of these age differences
- SDAD: standard deviation of age differences
- BSD: between-subject standard deviation of age differences
- WSD: within-subject standard deviation of age differences
- slope.male: slope from linear mixed effect model fitting
- intercept.male: intercept from linear mixed effect model fitting
The following age mixing characteristics are computed for the entire population in partnership between 35 and 40 simulation time.
Note that we took the age of a man and substract the age of his partner (woman), hence we have suffix “.male” on these measurements.
dr.agemixstat <- dr %>%
select("R.AAD.male", "R.SDAD.male", "R.slope.male", "R.WSD.male", "R.BSD.male" , "R.intercept.male" )
pop.R.AAD.male <- round(quant.med(dr.agemixstat$R.AAD.male), digits = 3)
pop.R.SDAD.male <- round(quant.med(dr.agemixstat$R.SDAD.male), digits = 3)
pop.R.slope.male <- round(quant.med(dr.agemixstat$R.slope.male), digits = 3)
pop.R.WSD.male <- round(quant.med(dr.agemixstat$R.WSD.male), digits = 3)
pop.R.BSD.male <- round(quant.med(dr.agemixstat$R.BSD.male), digits = 3)
pop.R.intercept.male <- round(quant.med(dr.agemixstat$R.intercept.male), digits = 3)
age.mix.F <- c(pop.R.AAD.male[2], pop.R.SDAD.male[2], pop.R.BSD.male[2],
pop.R.WSD.male[2], pop.R.slope.male[2], pop.R.intercept.male[2])
age.mix.L <- c(pop.R.AAD.male[1], pop.R.SDAD.male[1], pop.R.BSD.male[1],
pop.R.WSD.male[1], pop.R.slope.male[1], pop.R.intercept.male[1])
age.mix.U <- c(pop.R.AAD.male[3], pop.R.SDAD.male[3], pop.R.BSD.male[3],
pop.R.WSD.male[3], pop.R.slope.male[3], pop.R.intercept.male[3])
param.name <- c("AAD.male", "SDAD.male", "BSD.male" , "WSD.male", "slope.male", "intercept.male" )
age.mixing.pop <- data.frame(param.name, age.mix.L, age.mix.F, age.mix.U)
colnames(age.mixing.pop) <- c("param", "lower.Q1", "med", "upper.Q3")
age.mixing.pop %>%
kable() %>%
kable_styling("striped") | param | lower.Q1 | med | upper.Q3 |
|---|---|---|---|
| AAD.male | 13.679 | 13.966 | 14.275 |
| SDAD.male | 6.042 | 6.223 | 6.402 |
| BSD.male | 2.213 | 2.313 | 2.392 |
| WSD.male | 1.730 | 1.797 | 1.870 |
| slope.male | 0.315 | 0.334 | 0.351 |
| intercept.male | -2.872 | -2.596 | -2.280 |
write.csv(age.mixing.pop, file = "/home/david/age_mixing_patterns_phylogenetic/results/MAR_a/Table_a_5_Age_Mixing_Population_Level.csv")The results in the table above show that the median values of the average age difference (AAD) between men and women is around 14 years at population level which is almost 4 years far from mean of preferred age differences distribution for men and women. Its standard deviation (SDAD) is slightly more than 6 years, which is 1 year far from the value of standard deviation of preferred age differences distribution for men and women. We can see that the statistics of simulation study set up are reflecting here. [** is it correct, the assumption is that AAD ~ mu + sigma**]
1.3.2.2 True age mixing patterns in different sequence coverage scenarios of partnerships of infected and sampled invdividuals - MCAR
The table shows true median values of age mixing patterns (in relationships) of selected indiviuals (MCAR) in difference sequence coverage scenarios. These selecetd individuals are HIV positive, the measurement below assess their age mixing pattenrs within their sexual partnerships.
# MAR
d.MAR <- dr %>%
select(contains("MAR.a."))
d.MAR.cov.35 <- d.MAR %>%
select(contains("cov.MAR.a.35."))
d.MAR.cov.40 <- d.MAR %>%
select(contains("cov.MAR.a.40."))
d.MAR.cov.45 <- d.MAR %>%
select(contains("cov.MAR.a.45."))
d.MAR.cov.50 <- d.MAR %>%
select(contains("cov.MAR.a.50."))
d.MAR.cov.55 <- d.MAR %>%
select(contains("cov.MAR.a.55."))
d.MAR.cov.60 <- d.MAR %>%
select(contains("cov.MAR.a.60."))
d.MAR.cov.65 <- d.MAR %>%
select(contains("cov.MAR.a.65."))
d.MAR.cov.70 <- d.MAR %>%
select(contains("cov.MAR.a.70."))
d.MAR.cov.75 <- d.MAR %>%
select(contains("cov.MAR.a.75."))
d.MAR.cov.80 <- d.MAR %>%
select(contains("cov.MAR.a.80."))
d.MAR.cov.85 <- d.MAR %>%
select(contains("cov.MAR.a.85."))
d.MAR.cov.90 <- d.MAR %>%
select(contains("cov.MAR.a.90."))
d.MAR.cov.95 <- d.MAR %>%
select(contains("cov.MAR.a.95."))
d.MAR.cov.100 <- dr %>%
select(contains("cov.MCAR.100."))
# Age mixing statistics in transmission networks --------------------------
# True age mix in different age mix scenarios
dr.trans.agemix.MAR.cov.35 <- d.MAR.cov.35 %>%
select(contains(".T."))
dr.trans.agemix.MAR.cov.40 <- d.MAR.cov.40 %>%
select(contains(".T."))
dr.trans.agemix.MAR.cov.45 <- d.MAR.cov.45 %>%
select(contains(".T."))
dr.trans.agemix.MAR.cov.50 <- d.MAR.cov.50 %>%
select(contains(".T."))
dr.trans.agemix.MAR.cov.55 <- d.MAR.cov.55 %>%
select(contains(".T."))
dr.trans.agemix.MAR.cov.60 <- d.MAR.cov.60 %>%
select(contains(".T."))
dr.trans.agemix.MAR.cov.65 <- d.MAR.cov.65 %>%
select(contains(".T."))
dr.trans.agemix.MAR.cov.70 <- d.MAR.cov.70 %>%
select(contains(".T."))
dr.trans.agemix.MAR.cov.75 <- d.MAR.cov.75 %>%
select(contains(".T."))
dr.trans.agemix.MAR.cov.80 <- d.MAR.cov.80 %>%
select(contains(".T."))
dr.trans.agemix.MAR.cov.85 <- d.MAR.cov.85 %>%
select(contains(".T."))
dr.trans.agemix.MAR.cov.90 <- d.MAR.cov.90 %>%
select(contains(".T."))
dr.trans.agemix.MAR.cov.95 <- d.MAR.cov.95 %>%
select(contains(".T."))
# Age mixing in transmission
T.35.AAD.male <- quant.med(dr.trans.agemix.MAR.cov.35[,1])
T.35.SDAD.male <- quant.med(dr.trans.agemix.MAR.cov.35[,2])
T.35.slope.male <- quant.med(dr.trans.agemix.MAR.cov.35[,3])
T.35.WSD.male <- quant.med(dr.trans.agemix.MAR.cov.35[,4])
T.35.BSD.male <- quant.med(dr.trans.agemix.MAR.cov.35[,5])
T.35.intercept.male <- quant.med(dr.trans.agemix.MAR.cov.35[,6])
T.40.AAD.male <- quant.med(dr.trans.agemix.MAR.cov.40[,1])
T.40.SDAD.male <- quant.med(dr.trans.agemix.MAR.cov.40[,2])
T.40.slope.male <- quant.med(dr.trans.agemix.MAR.cov.40[,3])
T.40.WSD.male <- quant.med(dr.trans.agemix.MAR.cov.40[,4])
T.40.BSD.male <- quant.med(dr.trans.agemix.MAR.cov.40[,5])
T.40.intercept.male <- quant.med(dr.trans.agemix.MAR.cov.40[,6])
T.45.AAD.male <- quant.med(dr.trans.agemix.MAR.cov.45[,1])
T.45.SDAD.male <- quant.med(dr.trans.agemix.MAR.cov.45[,2])
T.45.slope.male <- quant.med(dr.trans.agemix.MAR.cov.45[,3])
T.45.WSD.male <- quant.med(dr.trans.agemix.MAR.cov.45[,4])
T.45.BSD.male <- quant.med(dr.trans.agemix.MAR.cov.45[,5])
T.45.intercept.male <- quant.med(dr.trans.agemix.MAR.cov.45[,6])
T.50.AAD.male <- quant.med(dr.trans.agemix.MAR.cov.50[,1])
T.50.SDAD.male <- quant.med(dr.trans.agemix.MAR.cov.50[,2])
T.50.slope.male <- quant.med(dr.trans.agemix.MAR.cov.50[,3])
T.50.WSD.male <- quant.med(dr.trans.agemix.MAR.cov.50[,4])
T.50.BSD.male <- quant.med(dr.trans.agemix.MAR.cov.50[,5])
T.50.intercept.male <- quant.med(dr.trans.agemix.MAR.cov.50[,6])
T.55.AAD.male <- quant.med(dr.trans.agemix.MAR.cov.55[,1])
T.55.SDAD.male <- quant.med(dr.trans.agemix.MAR.cov.55[,2])
T.55.slope.male <- quant.med(dr.trans.agemix.MAR.cov.55[,3])
T.55.WSD.male <- quant.med(dr.trans.agemix.MAR.cov.55[,4])
T.55.BSD.male <- quant.med(dr.trans.agemix.MAR.cov.55[,5])
T.55.intercept.male <- quant.med(dr.trans.agemix.MAR.cov.55[,6])
T.60.AAD.male <- quant.med(dr.trans.agemix.MAR.cov.60[,1])
T.60.SDAD.male <- quant.med(dr.trans.agemix.MAR.cov.60[,2])
T.60.slope.male <- quant.med(dr.trans.agemix.MAR.cov.60[,3])
T.60.WSD.male <- quant.med(dr.trans.agemix.MAR.cov.60[,4])
T.60.BSD.male <- quant.med(dr.trans.agemix.MAR.cov.60[,5])
T.60.intercept.male <- quant.med(dr.trans.agemix.MAR.cov.60[,6])
T.65.AAD.male <- quant.med(dr.trans.agemix.MAR.cov.65[,1])
T.65.SDAD.male <- quant.med(dr.trans.agemix.MAR.cov.65[,2])
T.65.slope.male <- quant.med(dr.trans.agemix.MAR.cov.65[,3])
T.65.WSD.male <- quant.med(dr.trans.agemix.MAR.cov.65[,4])
T.65.BSD.male <- quant.med(dr.trans.agemix.MAR.cov.65[,5])
T.65.intercept.male <- quant.med(dr.trans.agemix.MAR.cov.65[,6])
T.70.AAD.male <- quant.med(dr.trans.agemix.MAR.cov.70[,1])
T.70.SDAD.male <- quant.med(dr.trans.agemix.MAR.cov.70[,2])
T.70.slope.male <- quant.med(dr.trans.agemix.MAR.cov.70[,3])
T.70.WSD.male <- quant.med(dr.trans.agemix.MAR.cov.70[,4])
T.70.BSD.male <- quant.med(dr.trans.agemix.MAR.cov.70[,5])
T.70.intercept.male <- quant.med(dr.trans.agemix.MAR.cov.70[,6])
T.75.AAD.male <- quant.med(dr.trans.agemix.MAR.cov.75[,1])
T.75.SDAD.male <- quant.med(dr.trans.agemix.MAR.cov.75[,2])
T.75.slope.male <- quant.med(dr.trans.agemix.MAR.cov.75[,3])
T.75.WSD.male <- quant.med(dr.trans.agemix.MAR.cov.75[,4])
T.75.BSD.male <- quant.med(dr.trans.agemix.MAR.cov.75[,5])
T.75.intercept.male <- quant.med(dr.trans.agemix.MAR.cov.75[,6])
T.80.AAD.male <- quant.med(dr.trans.agemix.MAR.cov.80[,1])
T.80.SDAD.male <- quant.med(dr.trans.agemix.MAR.cov.80[,2])
T.80.slope.male <- quant.med(dr.trans.agemix.MAR.cov.80[,3])
T.80.WSD.male <- quant.med(dr.trans.agemix.MAR.cov.80[,4])
T.80.BSD.male <- quant.med(dr.trans.agemix.MAR.cov.80[,5])
T.80.intercept.male <- quant.med(dr.trans.agemix.MAR.cov.80[,6])
T.85.AAD.male <- quant.med(dr.trans.agemix.MAR.cov.85[,1])
T.85.SDAD.male <- quant.med(dr.trans.agemix.MAR.cov.85[,2])
T.85.slope.male <- quant.med(dr.trans.agemix.MAR.cov.85[,3])
T.85.WSD.male <- quant.med(dr.trans.agemix.MAR.cov.85[,4])
T.85.BSD.male <- quant.med(dr.trans.agemix.MAR.cov.85[,5])
T.85.intercept.male <- quant.med(dr.trans.agemix.MAR.cov.85[,6])
T.90.AAD.male <- quant.med(dr.trans.agemix.MAR.cov.90[,1])
T.90.SDAD.male <- quant.med(dr.trans.agemix.MAR.cov.90[,2])
T.90.slope.male <- quant.med(dr.trans.agemix.MAR.cov.90[,3])
T.90.WSD.male <- quant.med(dr.trans.agemix.MAR.cov.90[,4])
T.90.BSD.male <- quant.med(dr.trans.agemix.MAR.cov.90[,5])
T.90.intercept.male <- quant.med(dr.trans.agemix.MAR.cov.90[,6])
T.95.AAD.male <- quant.med(dr.trans.agemix.MAR.cov.95[,1])
T.95.SDAD.male <- quant.med(dr.trans.agemix.MAR.cov.95[,2])
T.95.slope.male <- quant.med(dr.trans.agemix.MAR.cov.95[,3])
T.95.WSD.male <- quant.med(dr.trans.agemix.MAR.cov.95[,4])
T.95.BSD.male <- quant.med(dr.trans.agemix.MAR.cov.95[,5])
T.95.intercept.male <- quant.med(dr.trans.agemix.MAR.cov.95[,6])
age.mix.stats <- matrix(c(T.35.AAD.male[2], T.40.AAD.male[2],
T.45.AAD.male[2], T.50.AAD.male[2],
T.55.AAD.male[2], T.60.AAD.male[2],
T.65.AAD.male[2], T.70.AAD.male[2],
T.75.AAD.male[2], T.80.AAD.male[2],
T.85.AAD.male[2], T.90.AAD.male[2],
T.95.AAD.male[2], pop.R.AAD.male[2],
T.35.SDAD.male[2], T.40.SDAD.male[2],
T.45.SDAD.male[2], T.50.SDAD.male[2],
T.55.SDAD.male[2], T.60.SDAD.male[2],
T.65.SDAD.male[2], T.70.SDAD.male[2],
T.75.SDAD.male[2], T.80.SDAD.male[2],
T.85.SDAD.male[2], T.90.SDAD.male[2],
T.95.SDAD.male[2], pop.R.SDAD.male[2],
T.35.BSD.male[2], T.40.BSD.male[2],
T.45.BSD.male[2], T.50.BSD.male[2],
T.55.BSD.male[2], T.60.BSD.male[2],
T.65.BSD.male[2], T.70.BSD.male[2],
T.75.BSD.male[2], T.80.BSD.male[2],
T.85.BSD.male[2], T.90.BSD.male[2],
T.95.BSD.male[2], pop.R.BSD.male[2],
T.35.WSD.male[2], T.40.WSD.male[2],
T.45.WSD.male[2], T.50.WSD.male[2],
T.55.WSD.male[2], T.60.WSD.male[2],
T.65.WSD.male[2], T.70.WSD.male[2],
T.75.WSD.male[2], T.80.WSD.male[2],
T.85.WSD.male[2], T.90.WSD.male[2],
T.95.WSD.male[2], pop.R.WSD.male[2],
T.35.slope.male[2], T.40.slope.male[2],
T.45.slope.male[2], T.50.slope.male[2],
T.55.slope.male[2], T.60.slope.male[2],
T.65.slope.male[2], T.70.slope.male[2],
T.75.slope.male[2], T.80.slope.male[2],
T.85.slope.male[2], T.90.slope.male[2],
T.95.slope.male[2], pop.R.slope.male[2],
T.35.intercept.male[2], T.40.intercept.male[2],
T.45.intercept.male[2], T.50.intercept.male[2],
T.55.intercept.male[2], T.60.intercept.male[2],
T.65.intercept.male[2], T.70.intercept.male[2],
T.75.intercept.male[2], T.80.intercept.male[2],
T.85.intercept.male[2], T.90.intercept.male[2],
T.95.intercept.male[2], pop.R.intercept.male[2]
),
ncol = 14,
byrow = TRUE)
age.mix.stats <- round(age.mix.stats, digits = 2)
colnames(age.mix.stats) <- c("cov.35", "cov.40", "cov.45",
"cov.50", "cov.55", "cov.60",
"cov.65", "cov.70", "cov.75",
"cov.80", "cov.85", "cov.90",
"cov.95", "true_100")
rownames(age.mix.stats) <- c("AAD.male", "SDAD.male", "BSD.male", "WSD.male", "slope.male", "intercept.male")
age.mix.stats %>%
kable() %>%
kable_styling("striped")| cov.35 | cov.40 | cov.45 | cov.50 | cov.55 | cov.60 | cov.65 | cov.70 | cov.75 | cov.80 | cov.85 | cov.90 | cov.95 | true_100 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| AAD.male | 9.87 | 9.82 | 9.92 | 10.03 | 10.05 | 10.20 | 10.27 | 10.39 | 10.46 | 10.54 | 10.70 | 10.80 | 10.91 | 13.97 |
| SDAD.male | 6.92 | 6.90 | 6.94 | 6.92 | 6.91 | 6.89 | 6.85 | 6.85 | 6.81 | 6.79 | 6.79 | 6.76 | 6.73 | 6.22 |
| BSD.male | 1.16 | 1.11 | 1.12 | 1.18 | 1.17 | 1.19 | 1.18 | 1.19 | 1.25 | 1.24 | 1.24 | 1.26 | 1.26 | 2.31 |
| WSD.male | 1.67 | 1.69 | 1.66 | 1.69 | 1.68 | 1.69 | 1.69 | 1.68 | 1.69 | 1.68 | 1.69 | 1.68 | 1.69 | 1.80 |
| slope.male | 0.14 | 0.15 | 0.14 | 0.15 | 0.15 | 0.15 | 0.15 | 0.16 | 0.16 | 0.16 | 0.16 | 0.17 | 0.17 | 0.33 |
| intercept.male | -0.12 | -0.13 | -0.10 | -0.18 | -0.19 | -0.21 | -0.21 | -0.31 | -0.33 | -0.38 | -0.41 | -0.46 | -0.53 | -2.60 |
write.csv(age.mix.stats, file = "/home/david/age_mixing_patterns_phylogenetic/results/MAR_a/Table_a_6_Age_Mixing_Sampling_Coverages.csv")The median value of AAD is one year apart from the true value at 100% sampling coverage (13.97), the SDAD still in same range (aroung 6) as at 100% sampling coverage.
Note that the increase in sampling (sequence) coverage does not have an obvious effect on statistics of age mixing patetrns of partnership of infected individuals. There is no statistics from low coverage which can be greater in magnitude than true values at 100% sampling coverage except for SDAD (values of SDAD at low sampling coverage can be greater compared to 100% sampling coverage).
1.3.2.3 Difference between true values of age mixing at population level and these from sampling scenarios in MCAR
When we compute the relative error between median of true values and these obtained in different sequence scenarios of age mixing statistics
\[\frac{(V_{true_{100}} – V_{true_{cov}})}{V_{true_{100}}}\]
This is the difference of true population level age mixing patterns in overall partnerships and true age mixing patterns in different sequence coverage scenarios of partnerships of infected and sampled invdividuals, which shows us how far are statistics of age mixing patterne in partnership for overall population and these of sub-population of infected individuals.
d.AAD.male <- (age.mix.stats[1,14] - age.mix.stats[1,])/age.mix.stats[1,14]
d.SDAD.male <- (age.mix.stats[2,14] - age.mix.stats[2,])/age.mix.stats[2,14]
d.slope.male <- (age.mix.stats[3,14] - age.mix.stats[3,])/age.mix.stats[3,14]
d.WSD.male <- (age.mix.stats[4,14] - age.mix.stats[4,])/age.mix.stats[4,14]
d.BSD.male <- (age.mix.stats[5,14] - age.mix.stats[5,])/age.mix.stats[5,14]
d.interc.male <- (age.mix.stats[6,14] - age.mix.stats[6,])/age.mix.stats[6,14]
diff.cov.true.age.mix.stats <- matrix(c(d.AAD.male, d.SDAD.male, d.BSD.male,
d.WSD.male, d.slope.male, d.interc.male),
ncol = 14,
byrow = TRUE)
colnames(diff.cov.true.age.mix.stats) <- c("35", "40", "45",
"50", "55", "60",
"65", "70", "75",
"80", "85", "90",
"95", "true_100")
rownames(diff.cov.true.age.mix.stats) <- c("d.AAD.male", "d.SDAD.male", "d.BSD.male", "d.WSD.male", "d.slope.male", "d.intercept.male")
error.age.mix.AAD.male <- data.frame(x=paste(c(seq(from=35, to=95, by=5))),
F = c(as.numeric(diff.cov.true.age.mix.stats[1,][-14])))
error.age.mix.AAD.male$parameter <- "AAD.male"
error.age.mix.SDAD.male <- data.frame(x=paste(c(seq(from=35, to=95, by=5))),
F = c(as.numeric(diff.cov.true.age.mix.stats[2,][-14])))
error.age.mix.SDAD.male$parameter <- "SDAD.male"
error.age.mix.slope.male <- data.frame(x=paste(c(seq(from=35, to=95, by=5))),
F = c(as.numeric(diff.cov.true.age.mix.stats[3,][-14])))
error.age.mix.slope.male$parameter <- "slope.male"
error.age.mix.WSD.male <- data.frame(x=paste(c(seq(from=35, to=95, by=5))),
F = c(as.numeric(diff.cov.true.age.mix.stats[4,][-14])))
error.age.mix.WSD.male$parameter <- "WSD.male"
error.age.mix.BSD.male <- data.frame(x=paste(c(seq(from=35, to=95, by=5))),
F = c(as.numeric(diff.cov.true.age.mix.stats[5,][-14])))
error.age.mix.BSD.male$parameter <- "BSD.male"
error.age.mix.intercept.male <- data.frame(x=paste(c(seq(from=35, to=95, by=5))),
F = c(as.numeric(diff.cov.true.age.mix.stats[6,][-14])))
error.age.mix.intercept.male$parameter <- "intercept.male"
errors.age.mixing <- rbind(error.age.mix.AAD.male, error.age.mix.BSD.male,
error.age.mix.SDAD.male,error.age.mix.WSD.male,
error.age.mix.intercept.male, error.age.mix.slope.male)
# plots.errors.age.mix <- ggplot(errors.age.mixing, aes(x=x, y=F, colour=parameter, group = parameter)) +
# # geom_errorbar(aes(ymin=L, ymax=U), width=.1) +
# geom_line(size=1) +
# geom_point() +
# xlab("Sampling Coverage") + ylab("Error")
#
# plots.errors.age.mix
colnames(errors.age.mixing) <- c("cov", "val", "Parameter")
plots.errors.age.mix <- ggplot(errors.age.mixing, aes(x=cov, y=val, group = Parameter)) +
# geom_errorbar(aes(ymin=L, ymax=U), width=.1) +
geom_line(aes(linetype=Parameter, color=Parameter))+ # , size=parameter
geom_point(aes(color=Parameter))+ # , size=parameter
scale_color_manual(values=c('#FF0000FF','#1A0808', '#00FF00', '#3CEFEF', '#1F4BC6', '#FF9900'))+
# theme(legend.position="top")+
xlab("Sampling Coverage (%)") + ylab("Error value for age mixing parameters")
print(plots.errors.age.mix)
ggsave(filename = "Plot_a_3_error_age_mixing.pdf",
plot = plots.errors.age.mix,
path = "/home/david/age_mixing_patterns_phylogenetic/results/MAR_a",
width = 26, height = 15, units = "cm")The error for WSD.male is around 0.05 and SDAD.male being below zero at almost 0.05 in absolute value, AAD.male turns around 0.1, BSD.male and slope.male varies between 0.3 and 0.4 (at highest sampling coverage the slope being on top), and the intercept.male turns aroung 0.5. All the variations of these measurements across different sequence scenarios show no variation with the increase of sampling coverage.
Overall, in terms of error magnitude we can classify from the lowest to the highest: SDAD.male, WSD.male, AAD.male, BSD.male, slope.male, and intercept.male. And we can conclude that sampling coverage does not affect results.
2 Computing transmission clusters
HIV transmission clusters were identified in the phylogenetic trees based on high support for the grouping and low within cluster genetic distance with Cluster Picker software. The settings of Cluster Picker to compute transmission clusters were such that: the initial support threshold was set to 0.8 (used to split the tree into subtrees to reduce the number of computations, and it must be ≤ the main support threshold for clusters), the main support threshold for clusters was set to 0.7 (90% bootstrap support for clusters - this can be set to 0.7, 0.8 or 0.99 according to the literature), the genetic distance threshold for clusters was set to 0.045 (maximum 4.5 substitutions/site within clusters - this can be set to 0.015, or 0.03 according to the literature), and finally we set the option to output lists of clusters above a certain size which was 2.
2.1 Statistics of size of transmission clusters
Per each simulation for the existing 1120, we computed transmission cluster size statistics: mean, median, and standard deviation to have an idea on their size distribution. Here below, we present the median values of these statistics for overall 1120 simulations in different sampling coverage.
# Cluster sizes
dr.cl.size.MAR.cov.35 <- d.MAR.cov.35 %>%
select(contains("cl.size"))
dr.cl.size.MAR.cov.40 <- d.MAR.cov.40 %>%
select(contains("cl.size"))
dr.cl.size.MAR.cov.45 <- d.MAR.cov.45 %>%
select(contains("cl.size"))
dr.cl.size.MAR.cov.50 <- d.MAR.cov.50 %>%
select(contains("cl.size"))
dr.cl.size.MAR.cov.55 <- d.MAR.cov.55 %>%
select(contains("cl.size"))
dr.cl.size.MAR.cov.60 <- d.MAR.cov.60 %>%
select(contains("cl.size"))
dr.cl.size.MAR.cov.65 <- d.MAR.cov.65 %>%
select(contains("cl.size"))
dr.cl.size.MAR.cov.70 <- d.MAR.cov.70 %>%
select(contains("cl.size"))
dr.cl.size.MAR.cov.75 <- d.MAR.cov.75 %>%
select(contains("cl.size"))
dr.cl.size.MAR.cov.80 <- d.MAR.cov.80 %>%
select(contains("cl.size"))
dr.cl.size.MAR.cov.85 <- d.MAR.cov.85 %>%
select(contains("cl.size"))
dr.cl.size.MAR.cov.90 <- d.MAR.cov.90 %>%
select(contains("cl.size"))
dr.cl.size.MAR.cov.95 <- d.MAR.cov.95 %>%
select(contains("cl.size"))
dr.cl.size.MAR.cov.100 <- d.MAR.cov.100 %>%
select(contains("cl.size"))
cl.size.mean.35 <- quant.med(dr.cl.size.MAR.cov.35$cov.MAR.a.35.mean.cl.size)
cl.size.med.35 <- quant.med(dr.cl.size.MAR.cov.35$cov.MAR.a.35.med.cl.size)
cl.size.sd.35 <- quant.med(dr.cl.size.MAR.cov.35$cov.MAR.a.35.sd.cl.size)
cl.size.mean.40 <- quant.med(dr.cl.size.MAR.cov.40$cov.MAR.a.40.mean.cl.size)
cl.size.med.40 <- quant.med(dr.cl.size.MAR.cov.40$cov.MAR.a.40.med.cl.size)
cl.size.sd.40 <- quant.med(dr.cl.size.MAR.cov.40$cov.MAR.a.40.sd.cl.size)
cl.size.mean.45 <- quant.med(dr.cl.size.MAR.cov.45$cov.MAR.a.45.mean.cl.size)
cl.size.med.45 <- quant.med(dr.cl.size.MAR.cov.45$cov.MAR.a.45.med.cl.size)
cl.size.sd.45 <- quant.med(dr.cl.size.MAR.cov.45$cov.MAR.a.45.sd.cl.size)
cl.size.mean.50 <- quant.med(dr.cl.size.MAR.cov.50$cov.MAR.a.50.mean.cl.size)
cl.size.med.50 <- quant.med(dr.cl.size.MAR.cov.50$cov.MAR.a.50.med.cl.size)
cl.size.sd.50 <- quant.med(dr.cl.size.MAR.cov.50$cov.MAR.a.50.sd.cl.size)
cl.size.mean.55 <- quant.med(dr.cl.size.MAR.cov.55$cov.MAR.a.55.mean.cl.size)
cl.size.med.55 <- quant.med(dr.cl.size.MAR.cov.55$cov.MAR.a.55.med.cl.size)
cl.size.sd.55 <- quant.med(dr.cl.size.MAR.cov.55$cov.MAR.a.55.sd.cl.size)
cl.size.mean.60 <- quant.med(dr.cl.size.MAR.cov.60$cov.MAR.a.60.mean.cl.size)
cl.size.med.60 <- quant.med(dr.cl.size.MAR.cov.60$cov.MAR.a.60.med.cl.size)
cl.size.sd.60 <- quant.med(dr.cl.size.MAR.cov.60$cov.MAR.a.60.sd.cl.size)
cl.size.mean.65 <- quant.med(dr.cl.size.MAR.cov.65$cov.MAR.a.65.mean.cl.size)
cl.size.med.65 <- quant.med(dr.cl.size.MAR.cov.65$cov.MAR.a.65.med.cl.size)
cl.size.sd.65 <- quant.med(dr.cl.size.MAR.cov.65$cov.MAR.a.65.sd.cl.size)
cl.size.mean.70 <- quant.med(dr.cl.size.MAR.cov.70$cov.MAR.a.70.mean.cl.size)
cl.size.med.70 <- quant.med(dr.cl.size.MAR.cov.70$cov.MAR.a.70.med.cl.size)
cl.size.sd.70 <- quant.med(dr.cl.size.MAR.cov.70$cov.MAR.a.70.sd.cl.size)
cl.size.mean.75 <- quant.med(dr.cl.size.MAR.cov.75$cov.MAR.a.75.mean.cl.size)
cl.size.med.75 <- quant.med(dr.cl.size.MAR.cov.75$cov.MAR.a.75.med.cl.size)
cl.size.sd.75 <- quant.med(dr.cl.size.MAR.cov.75$cov.MAR.a.75.sd.cl.size)
cl.size.mean.80 <- quant.med(dr.cl.size.MAR.cov.80$cov.MAR.a.80.mean.cl.size)
cl.size.med.80 <- quant.med(dr.cl.size.MAR.cov.80$cov.MAR.a.80.med.cl.size)
cl.size.sd.80 <- quant.med(dr.cl.size.MAR.cov.80$cov.MAR.a.80.sd.cl.size)
cl.size.mean.85 <- quant.med(dr.cl.size.MAR.cov.85$cov.MAR.a.85.mean.cl.size)
cl.size.med.85 <- quant.med(dr.cl.size.MAR.cov.85$cov.MAR.a.85.med.cl.size)
cl.size.sd.85 <- quant.med(dr.cl.size.MAR.cov.85$cov.MAR.a.85.sd.cl.size)
cl.size.mean.90 <- quant.med(dr.cl.size.MAR.cov.90$cov.MAR.a.90.mean.cl.size)
cl.size.med.90 <- quant.med(dr.cl.size.MAR.cov.90$cov.MAR.a.90.med.cl.size)
cl.size.sd.90 <- quant.med(dr.cl.size.MAR.cov.90$cov.MAR.a.90.sd.cl.size)
cl.size.mean.95 <- quant.med(dr.cl.size.MAR.cov.95$cov.MAR.a.95.mean.cl.size)
cl.size.med.95 <- quant.med(dr.cl.size.MAR.cov.95$cov.MAR.a.95.med.cl.size)
cl.size.sd.95 <- quant.med(dr.cl.size.MAR.cov.95$cov.MAR.a.95.sd.cl.size)
cl.size.mean.100 <- quant.med(dr.cl.size.MAR.cov.100$cov.MCAR.100.mean.cl.size)
cl.size.med.100 <- quant.med(dr.cl.size.MAR.cov.100$cov.MCAR.100.med.cl.size)
cl.size.sd.100 <- quant.med(dr.cl.size.MAR.cov.100$cov.MCAR.100.sd.cl.size)
cl.size.mean.df <- data.frame(x=c(paste(c(seq(from=35, to=95, by=5))), "true_100"),
F = c(cl.size.mean.35[2], cl.size.mean.40[2],
cl.size.mean.45[2], cl.size.mean.50[2],
cl.size.mean.55[2], cl.size.mean.60[2],
cl.size.mean.65[2], cl.size.mean.70[2],
cl.size.mean.75[2], cl.size.mean.80[2],
cl.size.mean.85[2], cl.size.mean.90[2],
cl.size.mean.95[2], cl.size.mean.100[2]),
L = c(cl.size.mean.35[1], cl.size.mean.40[1],
cl.size.mean.45[1], cl.size.mean.50[1],
cl.size.mean.55[1], cl.size.mean.60[1],
cl.size.mean.65[1], cl.size.mean.70[1],
cl.size.mean.75[1], cl.size.mean.80[1],
cl.size.mean.85[1], cl.size.mean.90[1],
cl.size.mean.95[1], cl.size.mean.100[1]),
U = c(cl.size.mean.35[3], cl.size.mean.40[3],
cl.size.mean.45[3], cl.size.mean.50[3],
cl.size.mean.55[3], cl.size.mean.60[3],
cl.size.mean.65[3], cl.size.mean.70[3],
cl.size.mean.75[3], cl.size.mean.80[3],
cl.size.mean.85[3], cl.size.mean.90[3],
cl.size.mean.95[3], cl.size.mean.100[3]))
cl.size.mean.df$parameter <- "Mean"
cl.size.med.df <- data.frame(x=c(paste(c(seq(from=35, to=95, by=5))), "true_100"),
F = c(cl.size.med.35[2], cl.size.med.40[2],
cl.size.med.45[2], cl.size.med.50[2],
cl.size.med.55[2], cl.size.med.60[2],
cl.size.med.65[2], cl.size.med.70[2],
cl.size.med.75[2], cl.size.med.80[2],
cl.size.med.85[2], cl.size.med.90[2],
cl.size.med.95[2], cl.size.med.100[2]),
L = c(cl.size.med.35[1], cl.size.med.40[1],
cl.size.med.45[1], cl.size.med.50[1],
cl.size.med.55[1], cl.size.med.60[1],
cl.size.med.65[1], cl.size.med.70[1],
cl.size.med.75[1], cl.size.med.80[1],
cl.size.med.85[1], cl.size.med.90[1],
cl.size.med.95[1], cl.size.med.100[1]),
U = c(cl.size.med.35[3], cl.size.med.40[3],
cl.size.med.45[3], cl.size.med.50[3],
cl.size.med.55[3], cl.size.med.60[3],
cl.size.med.65[3], cl.size.med.70[3],
cl.size.med.75[3], cl.size.med.80[3],
cl.size.med.85[3], cl.size.med.90[3],
cl.size.med.95[3], cl.size.med.100[3]))
cl.size.med.df$parameter <- "Median"
cl.size.sd.df <- data.frame(x=c(paste(c(seq(from=35, to=95, by=5))), "true_100"),
F = c(cl.size.sd.35[2], cl.size.sd.40[2],
cl.size.sd.45[2], cl.size.sd.50[2],
cl.size.sd.55[2], cl.size.sd.60[2],
cl.size.sd.65[2], cl.size.sd.70[2],
cl.size.sd.75[2], cl.size.sd.80[2],
cl.size.sd.85[2], cl.size.sd.90[2],
cl.size.sd.95[2], cl.size.sd.100[2]),
L = c(cl.size.sd.35[1], cl.size.sd.40[1],
cl.size.sd.45[1], cl.size.sd.50[1],
cl.size.sd.55[1], cl.size.sd.60[1],
cl.size.sd.65[1], cl.size.sd.70[1],
cl.size.sd.75[1], cl.size.sd.80[1],
cl.size.sd.85[1], cl.size.sd.90[1],
cl.size.sd.95[1], cl.size.sd.100[1]),
U = c(cl.size.sd.35[3], cl.size.sd.40[3],
cl.size.sd.45[3], cl.size.sd.50[3],
cl.size.sd.55[3], cl.size.sd.60[3],
cl.size.sd.65[3], cl.size.sd.70[3],
cl.size.sd.75[3], cl.size.sd.80[3],
cl.size.sd.85[3], cl.size.sd.90[3],
cl.size.sd.95[3], cl.size.sd.100[3]))
cl.size.sd.df$parameter <- "Standard_Dev"
# cl.number_phylo_pairings.df <- data.frame(x=c(seq(from=35, to=95, by=5), "cov.100"),
#
# F = c(cl.number_phylo_pairings.35[2], cl.number_phylo_pairings.40[2],
# cl.number_phylo_pairings.45[2], cl.number_phylo_pairings.50[2],
# cl.number_phylo_pairings.55[2], cl.number_phylo_pairings.60[2],
# cl.number_phylo_pairings.65[2], cl.number_phylo_pairings.70[2],
# cl.number_phylo_pairings.75[2], cl.number_phylo_pairings.80[2],
# cl.number_phylo_pairings.85[2], cl.number_phylo_pairings.90[2],
# cl.number_phylo_pairings.95[2], cl.number_phylo_pairings.100[2]),
#
# L = c(cl.number_phylo_pairings.35[1], cl.number_phylo_pairings.40[1],
# cl.number_phylo_pairings.45[1], cl.number_phylo_pairings.50[1],
# cl.number_phylo_pairings.55[1], cl.number_phylo_pairings.60[1],
# cl.number_phylo_pairings.65[1], cl.number_phylo_pairings.70[1],
# cl.number_phylo_pairings.75[1], cl.number_phylo_pairings.80[1],
# cl.number_phylo_pairings.85[1], cl.number_phylo_pairings.90[1],
# cl.number_phylo_pairings.95[1], cl.number_phylo_pairings.100[1]),
#
# U = c(cl.number_phylo_pairings.35[3], cl.number_phylo_pairings.40[3],
# cl.number_phylo_pairings.45[3], cl.number_phylo_pairings.50[3],
# cl.number_phylo_pairings.55[3], cl.number_phylo_pairings.60[3],
# cl.number_phylo_pairings.65[3], cl.number_phylo_pairings.70[3],
# cl.number_phylo_pairings.75[3], cl.number_phylo_pairings.80[3],
# cl.number_phylo_pairings.85[3], cl.number_phylo_pairings.90[3],
# cl.number_phylo_pairings.95[3], cl.number_phylo_pairings.100[3]))
#
# cl.number_phylo_pairings.df$param <- "pairings"
clust.size.stats <- rbind(cl.size.mean.df, cl.size.med.df, cl.size.sd.df) # , cl.number_phylo_pairings.df)
clust.size.stats$parameter <- factor(clust.size.stats$parameter)2.1.1 Number of pairings in transmission clusters
# pairings.clust.size.stats <- dplyr::filter(clust.size.stats, clust.size.stats$param=="pairings")
#
# pairings.clust <- pairings.clust.size.stats %>% transmute(seq.cov = x, lower.Q1 = L, med = F, upper.Q3 = U)
#
# pairings.clust %>%
# kable() %>%
# kable_styling("striped")
#
#
#
# plot.pairings.clust <- ggplot(pairings.clust, aes(x=seq.cov, y=med)) +
# geom_errorbar(aes(ymin=lower.Q1, ymax=upper.Q3), width=.1) +
# geom_line(size=.3) +
# geom_point() +
# xlab("Sampling Coverage") + ylab("Number of pairings")
#
#
# plot.pairings.clust2.1.2 Mean of transmission cluster size
mean.clust.size.stats <- dplyr::filter(clust.size.stats, clust.size.stats$parameter=="Mean")
mean.clust.size.stats <- mean.clust.size.stats %>% transmute(seq.cov = x, lower.Q1 = L, med = F, upper.Q3 = U)
mean.clust.size.stats %>%
kable() %>%
kable_styling("striped") | seq.cov | lower.Q1 | med | upper.Q3 |
|---|---|---|---|
| 35 | 2.615385 | 2.857143 | 3.214286 |
| 40 | 2.666667 | 2.916667 | 3.222222 |
| 45 | 2.714286 | 3.000000 | 3.333333 |
| 50 | 2.764706 | 3.074176 | 3.384615 |
| 55 | 2.823529 | 3.100000 | 3.414087 |
| 60 | 2.857143 | 3.187500 | 3.526316 |
| 65 | 2.920769 | 3.229021 | 3.523810 |
| 70 | 2.937500 | 3.246753 | 3.578947 |
| 75 | 2.977273 | 3.272727 | 3.636364 |
| 80 | 3.031061 | 3.318182 | 3.666667 |
| 85 | 3.054805 | 3.354839 | 3.672619 |
| 90 | 3.098171 | 3.388889 | 3.737681 |
| 95 | 3.123087 | 3.444444 | 3.827211 |
| true_100 | 3.416667 | 3.740741 | 4.108747 |
write.csv(mean.clust.size.stats, file = "/home/david/age_mixing_patterns_phylogenetic/results/MAR_a/Table_a_7_Mean_Clusters_Size.csv")
plot.mean.clust.size.stats <- ggplot(mean.clust.size.stats, aes(x=seq.cov, y=med)) +
geom_errorbar(aes(ymin=lower.Q1, ymax=upper.Q3), width=.1) +
geom_line(size=.3) +
geom_point() +
xlab("Sampling Coverage (%)") + ylab("Mean Cluster Size")
print(plot.mean.clust.size.stats)## geom_path: Each group consists of only one observation. Do you need to
## adjust the group aesthetic?
ggsave(filename = "Plot_a_4_Mean_Clusters_Size.pdf",
plot = plot.mean.clust.size.stats,
path = "/home/david/age_mixing_patterns_phylogenetic/results/MAR_a",
width = 16, height = 10, units = "cm")## geom_path: Each group consists of only one observation. Do you need to
## adjust the group aesthetic?2.1.3 Median of transmission cluster size
med.clust.size.stats <- dplyr::filter(clust.size.stats, clust.size.stats$parameter=="Median")
med.clust.size.stats <- med.clust.size.stats %>% transmute(seq.cov = x, lower.Q1 = L, med = F, upper.Q3 = U)
med.clust.size.stats %>%
kable() %>%
kable_styling("striped") | seq.cov | lower.Q1 | med | upper.Q3 |
|---|---|---|---|
| 35 | 2 | 2 | 2.5 |
| 40 | 2 | 2 | 2.5 |
| 45 | 2 | 2 | 2.5 |
| 50 | 2 | 2 | 2.5 |
| 55 | 2 | 2 | 2.5 |
| 60 | 2 | 2 | 3.0 |
| 65 | 2 | 2 | 2.5 |
| 70 | 2 | 2 | 2.5 |
| 75 | 2 | 2 | 3.0 |
| 80 | 2 | 2 | 3.0 |
| 85 | 2 | 2 | 3.0 |
| 90 | 2 | 2 | 3.0 |
| 95 | 2 | 2 | 3.0 |
| true_100 | 2 | 2 | 3.0 |
write.csv(med.clust.size.stats, file = "/home/david/age_mixing_patterns_phylogenetic/results/MAR_a/Table_a_8_Median_Clusters_Size.csv")
plot.med.clust.size.stats <- ggplot(med.clust.size.stats, aes(x=seq.cov, y=med)) +
geom_errorbar(aes(ymin=lower.Q1, ymax=upper.Q3), width=.1) +
geom_line(size=.3) +
geom_point() +
xlab("Sampling Coverage (%)") + ylab("Median Cluster Size")
print(plot.med.clust.size.stats)## geom_path: Each group consists of only one observation. Do you need to
## adjust the group aesthetic?
ggsave(filename = "Plot_a_5_Median_Clusters_Size.pdf",
plot = plot.med.clust.size.stats,
path = "/home/david/age_mixing_patterns_phylogenetic/results/MAR_a",
width = 16, height = 10, units = "cm")## geom_path: Each group consists of only one observation. Do you need to
## adjust the group aesthetic?2.1.4 Standard deviation of transmission cluster size
sd.clust.size.stats <- dplyr::filter(clust.size.stats, clust.size.stats$parameter=="Standard_Dev")
sd.clust.size.stats <- sd.clust.size.stats %>% transmute(seq.cov = x, lower.Q1 = L, med = F, upper.Q3 = U)
sd.clust.size.stats %>%
kable() %>%
kable_styling("striped") | seq.cov | lower.Q1 | med | upper.Q3 |
|---|---|---|---|
| 35 | 0.9607689 | 1.337493 | 1.843909 |
| 40 | 1.0328593 | 1.460092 | 1.959763 |
| 45 | 1.1547005 | 1.621903 | 2.182701 |
| 50 | 1.2754213 | 1.691392 | 2.290485 |
| 55 | 1.3480318 | 1.792830 | 2.405883 |
| 60 | 1.3988245 | 1.918734 | 2.580731 |
| 65 | 1.5394054 | 2.027135 | 2.595767 |
| 70 | 1.5895492 | 2.114166 | 2.717395 |
| 75 | 1.6269784 | 2.122601 | 2.814619 |
| 80 | 1.7015583 | 2.252708 | 2.852964 |
| 85 | 1.7842516 | 2.267787 | 3.008034 |
| 90 | 1.8405084 | 2.339130 | 3.091086 |
| 95 | 1.9004222 | 2.475356 | 3.184115 |
| true_100 | 2.5001953 | 3.128754 | 3.995274 |
write.csv(sd.clust.size.stats, file = "/home/david/age_mixing_patterns_phylogenetic/results/MAR_a/Table_a_9_Standard_Dev_Clusters_Size.csv")
plot.sd.clust.size.stats <- ggplot(sd.clust.size.stats, aes(x=seq.cov, y=med)) +
geom_errorbar(aes(ymin=lower.Q1, ymax=upper.Q3), width=.1) +
geom_line(size=.3) +
geom_point() +
xlab("Sampling Coverage (%)") + ylab("Stndard deviation Cluster Size")
print(plot.sd.clust.size.stats)## geom_path: Each group consists of only one observation. Do you need to
## adjust the group aesthetic?
ggsave(filename = "Plot_a_6_Standard_Dev_Clusters_Size.pdf",
plot = plot.sd.clust.size.stats,
path = "/home/david/age_mixing_patterns_phylogenetic/results/MAR_a",
width = 16, height = 10, units = "cm")## geom_path: Each group consists of only one observation. Do you need to
## adjust the group aesthetic?The mean and median of transmission cluster sizes increase with the sequence coverage, which is not the case for the standard deviation which remain almost constant with wide error bars.
# plot.clust.size.stats <- ggplot(clust.size.stats, aes(x=x, y=F, colour=param, group = param)) +
# geom_errorbar(aes(ymin=L, ymax=U), width=.1) +
# geom_line(size=.3) +
# geom_point() +
# xlab("Sampling Coverage") + ylab("Value")
# # ggtitle("Statistics of transmission clusters")
colnames(clust.size.stats) <- c("cov", "F", "L", "U", "Parameter")
plot.clust.size.stats <- ggplot(clust.size.stats, aes(x=cov, y=F, group = Parameter)) + # ggplot(clust.size.stats[-c(pairings)], aes(x=x, y=F, group = param)) +
# geom_errorbar(aes(ymin=L, ymax=U), width=.1) +
geom_line(aes(linetype=Parameter, color=Parameter))+ # , size=parameter
geom_point(aes(color=Parameter))+ # , size=parameter
scale_color_manual(values=c('#FF0000FF','#1A0808', '#00FF00', '#3CEFEF'))+ # , '#1F4BC6', '#FF9900
# theme(legend.position="top")+
xlab("Sampling Coverage (%)") + ylab("Value")
print(plot.clust.size.stats)
ggsave(filename = "Plot_a_7_Clusters_Size_Stats.pdf",
plot = plot.clust.size.stats,
path = "/home/david/age_mixing_patterns_phylogenetic/results/MAR_a",
width = 16, height = 10, units = "cm")3 Number of pairings in transmission clusters
We computed plausible pairings between men and women from the transmission clusters. In other words, we estimated plausible transmission network from a phylogenetictree. To build that plausible transmission network from the phylogenetic tree, we computed first the time to the most recent ancestor matrix (tMRCA), which is a contigency matrix. Thereafter, we filtered this matrix by gender, transmission cluster IDs, and a threshold value of tMRCA (7 years). This means that we have a pairing between individuals \(x_i\) and \(x_j\) if they are within same transmission cluster, have different gender, and their tMRCA does not exceed 7 years.
Since the simlation was performed 1120 times, the number of pairings presented in the tables below are median values.
We have in the following sections: true pairings which are computed from the transmission network from partnership and transmission records, and pairings estimated from phylogenetic tree.
3.1 True number of pairings at 100% sampling (sequence) coverage
Within 35 and 40 simulation time, if we consider the true pairings of all those who were HIV positive, we have the following table:
dr.cov.100 <- dr %>%
select(contains(".100"))
M.15.25.F.15.25.cov.100 <- quant.med(dr.cov.100$cov.MCAR.100.cl.true.M.15.25.F.15.25) # quant.med(dr.cov.100$cov.100.M.15.25.F.15.25)
M.25.40.F.15.25.cov.100 <- quant.med(dr.cov.100$cov.MCAR.100.cl.true.M.25.40.F.15.25) # quant.med(dr.cov.100$cov.100.M.25.40.F.15.25)
M.40.50.F.15.25.cov.100 <- quant.med(dr.cov.100$cov.MCAR.100.cl.true.M.40.50.F.15.25) # quant.med(dr.cov.100$cov.100.M.40.50.F.15.25)
M.15.25.F.25.40.cov.100 <- quant.med(dr.cov.100$cov.MCAR.100.cl.true.M.15.25.F.25.40) # quant.med(dr.cov.100$cov.100.M.15.25.F.25.40)
M.25.40.F.25.40.cov.100 <- quant.med(dr.cov.100$cov.MCAR.100.cl.true.M.25.40.F.25.40) # quant.med(dr.cov.100$cov.100.M.25.40.F.25.40)
M.40.50.F.25.40.cov.100 <- quant.med(dr.cov.100$cov.MCAR.100.cl.true.M.40.50.F.25.40) # quant.med(dr.cov.100$cov.100.M.40.50.F.25.40)
M.15.25.F.40.50.cov.100 <- quant.med(dr.cov.100$cov.MCAR.100.cl.true.M.15.25.F.40.50) # quant.med(dr.cov.100$cov.100.M.15.25.F.40.50)
M.25.40.F.40.50.cov.100 <- quant.med(dr.cov.100$cov.MCAR.100.cl.true.M.25.40.F.40.50) # quant.med(dr.cov.100$cov.100.M.25.40.F.40.50)
M.40.50.F.40.50.cov.100 <- quant.med(dr.cov.100$cov.MCAR.100.cl.true.M.40.50.F.40.50) # quant.med(dr.cov.100$cov.100.M.40.50.F.40.50)
true.cov.100.age.groups.table <- matrix(c((M.15.25.F.15.25.cov.100[2]), (M.15.25.F.25.40.cov.100[2]), (M.15.25.F.40.50.cov.100[2]),
(M.25.40.F.15.25.cov.100[2]), (M.25.40.F.25.40.cov.100[2]), (M.25.40.F.40.50.cov.100[2]),
(M.40.50.F.15.25.cov.100[2]), (M.40.50.F.25.40.cov.100[2]), (M.40.50.F.40.50.cov.100[2])),
ncol = 3,
byrow = TRUE)
colnames(true.cov.100.age.groups.table) <- c("Female.15.25", "Female.25.40", "Female.40.50")
rownames(true.cov.100.age.groups.table) <- c("Male.15.25", "Male.25.40", "Male.40.50")
true.cov.100.age.groups.table %>%
kable() %>%
kable_styling("striped") # Commented OCTOBER| Female.15.25 | Female.25.40 | Female.40.50 | |
|---|---|---|---|
| Male.15.25 | 7 | 0 | 0 |
| Male.25.40 | 33 | 7 | 0 |
| Male.40.50 | 17 | 15 | 0 |
write.csv(true.cov.100.age.groups.table, file = "/home/david/age_mixing_patterns_phylogenetic/results/MAR_a/Table_a_10_True_Pairings_at_100_Coverage.csv")Male within 25 and 40 were much pairing with women between 15 and 25 years old, followed by men in 40-50 and women between 15-25, and men in 40 - 50 and women in 25 - 40 of age.
3.2 True pairings at different sampling (sequence) coverage scenarios
Within 35 and 40 simulation time, if we consider the true pairings of a proportion of those who were HIV positive in different sampling (sequencing) coverage, we have the following table:
# Cov 35
M.15.25.F.15.25.MAR.cov.35 <- quant.med(d.MAR.cov.35$cov.MAR.a.35.cl.true.M.15.25.F.15.25)
M.25.40.F.15.25.MAR.cov.35 <- quant.med(d.MAR.cov.35$cov.MAR.a.35.cl.true.M.25.40.F.15.25)
M.40.50.F.15.25.MAR.cov.35 <- quant.med(d.MAR.cov.35$cov.MAR.a.35.cl.true.M.40.50.F.15.25)
M.15.25.F.25.40.MAR.cov.35 <- quant.med(d.MAR.cov.35$cov.MAR.a.35.cl.true.M.15.25.F.25.40)
M.25.40.F.25.40.MAR.cov.35 <- quant.med(d.MAR.cov.35$cov.MAR.a.35.cl.true.M.25.40.F.25.40)
M.40.50.F.25.40.MAR.cov.35 <- quant.med(d.MAR.cov.35$cov.MAR.a.35.cl.true.M.40.50.F.25.40)
M.15.25.F.40.50.MAR.cov.35 <- quant.med(d.MAR.cov.35$cov.MAR.a.35.cl.true.M.15.25.F.40.50)
M.25.40.F.40.50.MAR.cov.35 <- quant.med(d.MAR.cov.35$cov.MAR.a.35.cl.true.M.25.40.F.40.50)
M.40.50.F.40.50.MAR.cov.35 <- quant.med(d.MAR.cov.35$cov.MAR.a.35.cl.true.M.40.50.F.40.50)
# Cov 40
M.15.25.F.15.25.MAR.cov.40 <- quant.med(d.MAR.cov.40$cov.MAR.a.40.cl.true.M.15.25.F.15.25)
M.25.40.F.15.25.MAR.cov.40 <- quant.med(d.MAR.cov.40$cov.MAR.a.40.cl.true.M.25.40.F.15.25)
M.40.50.F.15.25.MAR.cov.40 <- quant.med(d.MAR.cov.40$cov.MAR.a.40.cl.true.M.40.50.F.15.25)
M.15.25.F.25.40.MAR.cov.40 <- quant.med(d.MAR.cov.40$cov.MAR.a.40.cl.true.M.15.25.F.25.40)
M.25.40.F.25.40.MAR.cov.40 <- quant.med(d.MAR.cov.40$cov.MAR.a.40.cl.true.M.25.40.F.25.40)
M.40.50.F.25.40.MAR.cov.40 <- quant.med(d.MAR.cov.40$cov.MAR.a.40.cl.true.M.40.50.F.25.40)
M.15.25.F.40.50.MAR.cov.40 <- quant.med(d.MAR.cov.40$cov.MAR.a.40.cl.true.M.15.25.F.40.50)
M.25.40.F.40.50.MAR.cov.40 <- quant.med(d.MAR.cov.40$cov.MAR.a.40.cl.true.M.25.40.F.40.50)
M.40.50.F.40.50.MAR.cov.40 <- quant.med(d.MAR.cov.40$cov.MAR.a.40.cl.true.M.40.50.F.40.50)
# Cov 45
M.15.25.F.15.25.MAR.cov.45 <- quant.med(d.MAR.cov.45$cov.MAR.a.45.cl.true.M.15.25.F.15.25)
M.25.40.F.15.25.MAR.cov.45 <- quant.med(d.MAR.cov.45$cov.MAR.a.45.cl.true.M.25.40.F.15.25)
M.40.50.F.15.25.MAR.cov.45 <- quant.med(d.MAR.cov.45$cov.MAR.a.45.cl.true.M.40.50.F.15.25)
M.15.25.F.25.40.MAR.cov.45 <- quant.med(d.MAR.cov.45$cov.MAR.a.45.cl.true.M.15.25.F.25.40)
M.25.40.F.25.40.MAR.cov.45 <- quant.med(d.MAR.cov.45$cov.MAR.a.45.cl.true.M.25.40.F.25.40)
M.40.50.F.25.40.MAR.cov.45 <- quant.med(d.MAR.cov.45$cov.MAR.a.45.cl.true.M.40.50.F.25.40)
M.15.25.F.40.50.MAR.cov.45 <- quant.med(d.MAR.cov.45$cov.MAR.a.45.cl.true.M.15.25.F.40.50)
M.25.40.F.40.50.MAR.cov.45 <- quant.med(d.MAR.cov.45$cov.MAR.a.45.cl.true.M.25.40.F.40.50)
M.40.50.F.40.50.MAR.cov.45 <- quant.med(d.MAR.cov.45$cov.MAR.a.45.cl.true.M.40.50.F.40.50)
# Cov 50
M.15.25.F.15.25.MAR.cov.50 <- quant.med(d.MAR.cov.50$cov.MAR.a.50.cl.true.M.15.25.F.15.25)
M.25.40.F.15.25.MAR.cov.50 <- quant.med(d.MAR.cov.50$cov.MAR.a.50.cl.true.M.25.40.F.15.25)
M.40.50.F.15.25.MAR.cov.50 <- quant.med(d.MAR.cov.50$cov.MAR.a.50.cl.true.M.40.50.F.15.25)
M.15.25.F.25.40.MAR.cov.50 <- quant.med(d.MAR.cov.50$cov.MAR.a.50.cl.true.M.15.25.F.25.40)
M.25.40.F.25.40.MAR.cov.50 <- quant.med(d.MAR.cov.50$cov.MAR.a.50.cl.true.M.25.40.F.25.40)
M.40.50.F.25.40.MAR.cov.50 <- quant.med(d.MAR.cov.50$cov.MAR.a.50.cl.true.M.40.50.F.25.40)
M.15.25.F.40.50.MAR.cov.50 <- quant.med(d.MAR.cov.50$cov.MAR.a.50.cl.true.M.15.25.F.40.50)
M.25.40.F.40.50.MAR.cov.50 <- quant.med(d.MAR.cov.50$cov.MAR.a.50.cl.true.M.25.40.F.40.50)
M.40.50.F.40.50.MAR.cov.50 <- quant.med(d.MAR.cov.50$cov.MAR.a.50.cl.true.M.40.50.F.40.50)
# Cov 55
M.15.25.F.15.25.MAR.cov.55 <- quant.med(d.MAR.cov.55$cov.MAR.a.55.cl.true.M.15.25.F.15.25)
M.25.40.F.15.25.MAR.cov.55 <- quant.med(d.MAR.cov.55$cov.MAR.a.55.cl.true.M.25.40.F.15.25)
M.40.50.F.15.25.MAR.cov.55 <- quant.med(d.MAR.cov.55$cov.MAR.a.55.cl.true.M.40.50.F.15.25)
M.15.25.F.25.40.MAR.cov.55 <- quant.med(d.MAR.cov.55$cov.MAR.a.55.cl.true.M.15.25.F.25.40)
M.25.40.F.25.40.MAR.cov.55 <- quant.med(d.MAR.cov.55$cov.MAR.a.55.cl.true.M.25.40.F.25.40)
M.40.50.F.25.40.MAR.cov.55 <- quant.med(d.MAR.cov.55$cov.MAR.a.55.cl.true.M.40.50.F.25.40)
M.15.25.F.40.50.MAR.cov.55 <- quant.med(d.MAR.cov.55$cov.MAR.a.55.cl.true.M.15.25.F.40.50)
M.25.40.F.40.50.MAR.cov.55 <- quant.med(d.MAR.cov.55$cov.MAR.a.55.cl.true.M.25.40.F.40.50)
M.40.50.F.40.50.MAR.cov.55 <- quant.med(d.MAR.cov.55$cov.MAR.a.55.cl.true.M.40.50.F.40.50)
# Cov 60
M.15.25.F.15.25.MAR.cov.60 <- quant.med(d.MAR.cov.60$cov.MAR.a.60.cl.true.M.15.25.F.15.25)
M.25.40.F.15.25.MAR.cov.60 <- quant.med(d.MAR.cov.60$cov.MAR.a.60.cl.true.M.25.40.F.15.25)
M.40.50.F.15.25.MAR.cov.60 <- quant.med(d.MAR.cov.60$cov.MAR.a.60.cl.true.M.40.50.F.15.25)
M.15.25.F.25.40.MAR.cov.60 <- quant.med(d.MAR.cov.60$cov.MAR.a.60.cl.true.M.15.25.F.25.40)
M.25.40.F.25.40.MAR.cov.60 <- quant.med(d.MAR.cov.60$cov.MAR.a.60.cl.true.M.25.40.F.25.40)
M.40.50.F.25.40.MAR.cov.60 <- quant.med(d.MAR.cov.60$cov.MAR.a.60.cl.true.M.40.50.F.25.40)
M.15.25.F.40.50.MAR.cov.60 <- quant.med(d.MAR.cov.60$cov.MAR.a.60.cl.true.M.15.25.F.40.50)
M.25.40.F.40.50.MAR.cov.60 <- quant.med(d.MAR.cov.60$cov.MAR.a.60.cl.true.M.25.40.F.40.50)
M.40.50.F.40.50.MAR.cov.60 <- quant.med(d.MAR.cov.60$cov.MAR.a.60.cl.true.M.40.50.F.40.50)
# Cov 65
M.15.25.F.15.25.MAR.cov.65 <- quant.med(d.MAR.cov.65$cov.MAR.a.65.cl.true.M.15.25.F.15.25)
M.25.40.F.15.25.MAR.cov.65 <- quant.med(d.MAR.cov.65$cov.MAR.a.65.cl.true.M.25.40.F.15.25)
M.40.50.F.15.25.MAR.cov.65 <- quant.med(d.MAR.cov.65$cov.MAR.a.65.cl.true.M.40.50.F.15.25)
M.15.25.F.25.40.MAR.cov.65 <- quant.med(d.MAR.cov.65$cov.MAR.a.65.cl.true.M.15.25.F.25.40)
M.25.40.F.25.40.MAR.cov.65 <- quant.med(d.MAR.cov.65$cov.MAR.a.65.cl.true.M.25.40.F.25.40)
M.40.50.F.25.40.MAR.cov.65 <- quant.med(d.MAR.cov.65$cov.MAR.a.65.cl.true.M.40.50.F.25.40)
M.15.25.F.40.50.MAR.cov.65 <- quant.med(d.MAR.cov.65$cov.MAR.a.65.cl.true.M.15.25.F.40.50)
M.25.40.F.40.50.MAR.cov.65 <- quant.med(d.MAR.cov.65$cov.MAR.a.65.cl.true.M.25.40.F.40.50)
M.40.50.F.40.50.MAR.cov.65 <- quant.med(d.MAR.cov.65$cov.MAR.a.65.cl.true.M.40.50.F.40.50)
# Cov 70
M.15.25.F.15.25.MAR.cov.70 <- quant.med(d.MAR.cov.70$cov.MAR.a.70.cl.true.M.15.25.F.15.25)
M.25.40.F.15.25.MAR.cov.70 <- quant.med(d.MAR.cov.70$cov.MAR.a.70.cl.true.M.25.40.F.15.25)
M.40.50.F.15.25.MAR.cov.70 <- quant.med(d.MAR.cov.70$cov.MAR.a.70.cl.true.M.40.50.F.15.25)
M.15.25.F.25.40.MAR.cov.70 <- quant.med(d.MAR.cov.70$cov.MAR.a.70.cl.true.M.15.25.F.25.40)
M.25.40.F.25.40.MAR.cov.70 <- quant.med(d.MAR.cov.70$cov.MAR.a.70.cl.true.M.25.40.F.25.40)
M.40.50.F.25.40.MAR.cov.70 <- quant.med(d.MAR.cov.70$cov.MAR.a.70.cl.true.M.40.50.F.25.40)
M.15.25.F.40.50.MAR.cov.70 <- quant.med(d.MAR.cov.70$cov.MAR.a.70.cl.true.M.15.25.F.40.50)
M.25.40.F.40.50.MAR.cov.70 <- quant.med(d.MAR.cov.70$cov.MAR.a.70.cl.true.M.25.40.F.40.50)
M.40.50.F.40.50.MAR.cov.70 <- quant.med(d.MAR.cov.70$cov.MAR.a.70.cl.true.M.40.50.F.40.50)
# Cov 75
M.15.25.F.15.25.MAR.cov.75 <- quant.med(d.MAR.cov.75$cov.MAR.a.75.cl.true.M.15.25.F.15.25)
M.25.40.F.15.25.MAR.cov.75 <- quant.med(d.MAR.cov.75$cov.MAR.a.75.cl.true.M.25.40.F.15.25)
M.40.50.F.15.25.MAR.cov.75 <- quant.med(d.MAR.cov.75$cov.MAR.a.75.cl.true.M.40.50.F.15.25)
M.15.25.F.25.40.MAR.cov.75 <- quant.med(d.MAR.cov.75$cov.MAR.a.75.cl.true.M.15.25.F.25.40)
M.25.40.F.25.40.MAR.cov.75 <- quant.med(d.MAR.cov.75$cov.MAR.a.75.cl.true.M.25.40.F.25.40)
M.40.50.F.25.40.MAR.cov.75 <- quant.med(d.MAR.cov.75$cov.MAR.a.75.cl.true.M.40.50.F.25.40)
M.15.25.F.40.50.MAR.cov.75 <- quant.med(d.MAR.cov.75$cov.MAR.a.75.cl.true.M.15.25.F.40.50)
M.25.40.F.40.50.MAR.cov.75 <- quant.med(d.MAR.cov.75$cov.MAR.a.75.cl.true.M.25.40.F.40.50)
M.40.50.F.40.50.MAR.cov.75 <- quant.med(d.MAR.cov.75$cov.MAR.a.75.cl.true.M.40.50.F.40.50)
# Cov 80
M.15.25.F.15.25.MAR.cov.80 <- quant.med(d.MAR.cov.80$cov.MAR.a.80.cl.true.M.15.25.F.15.25)
M.25.40.F.15.25.MAR.cov.80 <- quant.med(d.MAR.cov.80$cov.MAR.a.80.cl.true.M.25.40.F.15.25)
M.40.50.F.15.25.MAR.cov.80 <- quant.med(d.MAR.cov.80$cov.MAR.a.80.cl.true.M.40.50.F.15.25)
M.15.25.F.25.40.MAR.cov.80 <- quant.med(d.MAR.cov.80$cov.MAR.a.80.cl.true.M.15.25.F.25.40)
M.25.40.F.25.40.MAR.cov.80 <- quant.med(d.MAR.cov.80$cov.MAR.a.80.cl.true.M.25.40.F.25.40)
M.40.50.F.25.40.MAR.cov.80 <- quant.med(d.MAR.cov.80$cov.MAR.a.80.cl.true.M.40.50.F.25.40)
M.15.25.F.40.50.MAR.cov.80 <- quant.med(d.MAR.cov.80$cov.MAR.a.80.cl.true.M.15.25.F.40.50)
M.25.40.F.40.50.MAR.cov.80 <- quant.med(d.MAR.cov.80$cov.MAR.a.80.cl.true.M.25.40.F.40.50)
M.40.50.F.40.50.MAR.cov.80 <- quant.med(d.MAR.cov.80$cov.MAR.a.80.cl.true.M.40.50.F.40.50)
# Cov 85
M.15.25.F.15.25.MAR.cov.85 <- quant.med(d.MAR.cov.85$cov.MAR.a.85.cl.true.M.15.25.F.15.25)
M.25.40.F.15.25.MAR.cov.85 <- quant.med(d.MAR.cov.85$cov.MAR.a.85.cl.true.M.25.40.F.15.25)
M.40.50.F.15.25.MAR.cov.85 <- quant.med(d.MAR.cov.85$cov.MAR.a.85.cl.true.M.40.50.F.15.25)
M.15.25.F.25.40.MAR.cov.85 <- quant.med(d.MAR.cov.85$cov.MAR.a.85.cl.true.M.15.25.F.25.40)
M.25.40.F.25.40.MAR.cov.85 <- quant.med(d.MAR.cov.85$cov.MAR.a.85.cl.true.M.25.40.F.25.40)
M.40.50.F.25.40.MAR.cov.85 <- quant.med(d.MAR.cov.85$cov.MAR.a.85.cl.true.M.40.50.F.25.40)
M.15.25.F.40.50.MAR.cov.85 <- quant.med(d.MAR.cov.85$cov.MAR.a.85.cl.true.M.15.25.F.40.50)
M.25.40.F.40.50.MAR.cov.85 <- quant.med(d.MAR.cov.85$cov.MAR.a.85.cl.true.M.25.40.F.40.50)
M.40.50.F.40.50.MAR.cov.85 <- quant.med(d.MAR.cov.85$cov.MAR.a.85.cl.true.M.40.50.F.40.50)
# Cov 90
M.15.25.F.15.25.MAR.cov.90 <- quant.med(d.MAR.cov.90$cov.MAR.a.90.cl.true.M.15.25.F.15.25)
M.25.40.F.15.25.MAR.cov.90 <- quant.med(d.MAR.cov.90$cov.MAR.a.90.cl.true.M.25.40.F.15.25)
M.40.50.F.15.25.MAR.cov.90 <- quant.med(d.MAR.cov.90$cov.MAR.a.90.cl.true.M.40.50.F.15.25)
M.15.25.F.25.40.MAR.cov.90 <- quant.med(d.MAR.cov.90$cov.MAR.a.90.cl.true.M.15.25.F.25.40)
M.25.40.F.25.40.MAR.cov.90 <- quant.med(d.MAR.cov.90$cov.MAR.a.90.cl.true.M.25.40.F.25.40)
M.40.50.F.25.40.MAR.cov.90 <- quant.med(d.MAR.cov.90$cov.MAR.a.90.cl.true.M.40.50.F.25.40)
M.15.25.F.40.50.MAR.cov.90 <- quant.med(d.MAR.cov.90$cov.MAR.a.90.cl.true.M.15.25.F.40.50)
M.25.40.F.40.50.MAR.cov.90 <- quant.med(d.MAR.cov.90$cov.MAR.a.90.cl.true.M.25.40.F.40.50)
M.40.50.F.40.50.MAR.cov.90 <- quant.med(d.MAR.cov.90$cov.MAR.a.90.cl.true.M.40.50.F.40.50)
# Cov 95
M.15.25.F.15.25.MAR.cov.95 <- quant.med(d.MAR.cov.95$cov.MAR.a.95.cl.true.M.15.25.F.15.25)
M.25.40.F.15.25.MAR.cov.95 <- quant.med(d.MAR.cov.95$cov.MAR.a.95.cl.true.M.25.40.F.15.25)
M.40.50.F.15.25.MAR.cov.95 <- quant.med(d.MAR.cov.95$cov.MAR.a.95.cl.true.M.40.50.F.15.25)
M.15.25.F.25.40.MAR.cov.95 <- quant.med(d.MAR.cov.95$cov.MAR.a.95.cl.true.M.15.25.F.25.40)
M.25.40.F.25.40.MAR.cov.95 <- quant.med(d.MAR.cov.95$cov.MAR.a.95.cl.true.M.25.40.F.25.40)
M.40.50.F.25.40.MAR.cov.95 <- quant.med(d.MAR.cov.95$cov.MAR.a.95.cl.true.M.40.50.F.25.40)
M.15.25.F.40.50.MAR.cov.95 <- quant.med(d.MAR.cov.95$cov.MAR.a.95.cl.true.M.15.25.F.40.50)
M.25.40.F.40.50.MAR.cov.95 <- quant.med(d.MAR.cov.95$cov.MAR.a.95.cl.true.M.25.40.F.40.50)
M.40.50.F.40.50.MAR.cov.95 <- quant.med(d.MAR.cov.95$cov.MAR.a.95.cl.true.M.40.50.F.40.50)
# Agregated table of pairings: true
pairing_true_scenarios <- matrix(c(M.15.25.F.15.25.MAR.cov.35[2], M.15.25.F.15.25.MAR.cov.40[2],
M.15.25.F.15.25.MAR.cov.45[2], M.15.25.F.15.25.MAR.cov.50[2],
M.15.25.F.15.25.MAR.cov.55[2], M.15.25.F.15.25.MAR.cov.60[2],
M.15.25.F.15.25.MAR.cov.65[2], M.15.25.F.15.25.MAR.cov.70[2],
M.15.25.F.15.25.MAR.cov.75[2], M.15.25.F.15.25.MAR.cov.80[2],
M.15.25.F.15.25.MAR.cov.85[2], M.15.25.F.15.25.MAR.cov.90[2],
M.15.25.F.15.25.MAR.cov.95[2], M.15.25.F.15.25.cov.100[2],
M.25.40.F.15.25.MAR.cov.35[2], M.25.40.F.15.25.MAR.cov.40[2],
M.25.40.F.15.25.MAR.cov.45[2], M.25.40.F.15.25.MAR.cov.50[2],
M.25.40.F.15.25.MAR.cov.55[2], M.25.40.F.15.25.MAR.cov.60[2],
M.25.40.F.15.25.MAR.cov.65[2], M.25.40.F.15.25.MAR.cov.70[2],
M.25.40.F.15.25.MAR.cov.75[2], M.25.40.F.15.25.MAR.cov.80[2],
M.25.40.F.15.25.MAR.cov.85[2], M.25.40.F.15.25.MAR.cov.90[2],
M.25.40.F.15.25.MAR.cov.95[2], M.25.40.F.15.25.cov.100[2],
M.40.50.F.15.25.MAR.cov.35[2], M.40.50.F.15.25.MAR.cov.40[2],
M.40.50.F.15.25.MAR.cov.45[2], M.40.50.F.15.25.MAR.cov.50[2],
M.40.50.F.15.25.MAR.cov.55[2], M.40.50.F.15.25.MAR.cov.60[2],
M.40.50.F.15.25.MAR.cov.65[2], M.40.50.F.15.25.MAR.cov.70[2],
M.40.50.F.15.25.MAR.cov.75[2], M.40.50.F.15.25.MAR.cov.80[2],
M.40.50.F.15.25.MAR.cov.85[2], M.40.50.F.15.25.MAR.cov.90[2],
M.40.50.F.15.25.MAR.cov.95[2], M.40.50.F.15.25.cov.100[2],
M.15.25.F.25.40.MAR.cov.35[2], M.15.25.F.25.40.MAR.cov.40[2],
M.15.25.F.25.40.MAR.cov.45[2], M.15.25.F.25.40.MAR.cov.50[2],
M.15.25.F.25.40.MAR.cov.55[2], M.15.25.F.25.40.MAR.cov.60[2],
M.15.25.F.25.40.MAR.cov.65[2], M.15.25.F.25.40.MAR.cov.70[2],
M.15.25.F.25.40.MAR.cov.75[2], M.15.25.F.25.40.MAR.cov.80[2],
M.15.25.F.25.40.MAR.cov.85[2], M.15.25.F.25.40.MAR.cov.90[2],
M.15.25.F.25.40.MAR.cov.95[2], M.15.25.F.25.40.cov.100[2],
M.25.40.F.25.40.MAR.cov.35[2], M.25.40.F.25.40.MAR.cov.40[2],
M.25.40.F.25.40.MAR.cov.45[2], M.25.40.F.25.40.MAR.cov.50[2],
M.25.40.F.25.40.MAR.cov.55[2], M.25.40.F.25.40.MAR.cov.60[2],
M.25.40.F.25.40.MAR.cov.65[2], M.25.40.F.25.40.MAR.cov.70[2],
M.25.40.F.25.40.MAR.cov.75[2], M.25.40.F.25.40.MAR.cov.80[2],
M.25.40.F.25.40.MAR.cov.85[2], M.25.40.F.25.40.MAR.cov.90[2],
M.25.40.F.25.40.MAR.cov.95[2], M.25.40.F.25.40.cov.100[2],
M.40.50.F.25.40.MAR.cov.35[2], M.40.50.F.25.40.MAR.cov.40[2],
M.40.50.F.25.40.MAR.cov.45[2], M.40.50.F.25.40.MAR.cov.50[2],
M.40.50.F.25.40.MAR.cov.55[2], M.40.50.F.25.40.MAR.cov.60[2],
M.40.50.F.25.40.MAR.cov.65[2], M.40.50.F.25.40.MAR.cov.70[2],
M.40.50.F.25.40.MAR.cov.75[2], M.40.50.F.25.40.MAR.cov.80[2],
M.40.50.F.25.40.MAR.cov.85[2], M.40.50.F.25.40.MAR.cov.90[2],
M.40.50.F.25.40.MAR.cov.95[2], M.40.50.F.25.40.cov.100[2],
M.15.25.F.40.50.MAR.cov.35[2], M.15.25.F.40.50.MAR.cov.40[2],
M.15.25.F.40.50.MAR.cov.45[2], M.15.25.F.40.50.MAR.cov.50[2],
M.15.25.F.40.50.MAR.cov.55[2], M.15.25.F.40.50.MAR.cov.60[2],
M.15.25.F.40.50.MAR.cov.65[2], M.15.25.F.40.50.MAR.cov.70[2],
M.15.25.F.40.50.MAR.cov.75[2], M.15.25.F.40.50.MAR.cov.80[2],
M.15.25.F.40.50.MAR.cov.85[2], M.15.25.F.40.50.MAR.cov.90[2],
M.15.25.F.40.50.MAR.cov.95[2], M.15.25.F.40.50.cov.100[2],
M.25.40.F.40.50.MAR.cov.35[2], M.25.40.F.40.50.MAR.cov.40[2],
M.25.40.F.40.50.MAR.cov.45[2], M.25.40.F.40.50.MAR.cov.50[2],
M.25.40.F.40.50.MAR.cov.55[2], M.25.40.F.40.50.MAR.cov.60[2],
M.25.40.F.40.50.MAR.cov.65[2], M.25.40.F.40.50.MAR.cov.70[2],
M.25.40.F.40.50.MAR.cov.75[2], M.25.40.F.40.50.MAR.cov.80[2],
M.25.40.F.40.50.MAR.cov.85[2], M.25.40.F.40.50.MAR.cov.90[2],
M.25.40.F.40.50.MAR.cov.95[2], M.25.40.F.40.50.cov.100[2],
M.40.50.F.40.50.MAR.cov.35[2], M.40.50.F.40.50.MAR.cov.40[2],
M.40.50.F.40.50.MAR.cov.45[2], M.40.50.F.40.50.MAR.cov.50[2],
M.40.50.F.40.50.MAR.cov.55[2], M.40.50.F.40.50.MAR.cov.60[2],
M.40.50.F.40.50.MAR.cov.65[2], M.40.50.F.40.50.MAR.cov.70[2],
M.40.50.F.40.50.MAR.cov.75[2], M.40.50.F.40.50.MAR.cov.80[2],
M.40.50.F.40.50.MAR.cov.85[2], M.40.50.F.40.50.MAR.cov.90[2],
M.40.50.F.40.50.MAR.cov.95[2], M.40.50.F.40.50.cov.100[2]),
ncol = 14,
byrow = TRUE)
colnames(pairing_true_scenarios) <- c("35", "40", "45",
"50", "55", "60",
"65", "70", "75",
"80", "85", "90",
"95", "true_100")
rownames(pairing_true_scenarios) <- c("M.15.25.F.15.25", "M.25.40.F.15.25", "M.40.50.F.15.25",
"M.15.25.F.25.40", "M.25.40.F.25.40", "M.40.50.F.25.40",
"M.15.25.F.40.50", "M.25.40.F.40.50", "M.40.50.F.40.50")
pairing_true_scenarios %>%
kable() %>%
kable_styling("striped") # OK| 35 | 40 | 45 | 50 | 55 | 60 | 65 | 70 | 75 | 80 | 85 | 90 | 95 | true_100 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| M.15.25.F.15.25 | 1 | 2 | 2 | 3 | 3 | 3 | 3 | 4 | 4 | 4 | 4 | 5 | 5 | 7 |
| M.25.40.F.15.25 | 3 | 4 | 4 | 5 | 6 | 7 | 8 | 10 | 11 | 12 | 13 | 15 | 16 | 33 |
| M.40.50.F.15.25 | 1 | 1 | 1 | 2 | 2 | 2 | 3 | 3 | 4 | 4 | 5 | 5 | 6 | 17 |
| M.15.25.F.25.40 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| M.25.40.F.25.40 | 0 | 1 | 1 | 1 | 1 | 1 | 2 | 2 | 2 | 3 | 3 | 3 | 3 | 7 |
| M.40.50.F.25.40 | 1 | 1 | 1 | 2 | 2 | 3 | 3 | 3 | 4 | 4 | 5 | 5 | 5 | 15 |
| M.15.25.F.40.50 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| M.25.40.F.40.50 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| M.40.50.F.40.50 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
write.csv(pairing_true_scenarios, file = "/home/david/age_mixing_patterns_phylogenetic/results/MAR_a/Table_a_11_True_Pairings_at_35_95_Coverage.csv")Like in the previous table of 100% sampling coverage, male within 25 and 40 were much pairing with women between 15 and 25 years old, followed by men in 40-50 and women between 15-25, and men in 40 - 50 and women in 25 - 40 of age. In addition, we can see that as the sequence coverage increase the number of pairings becomes close to the true values at 100% coverage.
3.3 Pairings inferred from transmission clusters of a phylogenetic tree
Within 35 and 40 simulation time, if we consider pairings built from phylogenetic tree’s transmission clusters in different sampling (sequencing) coverage, we have the following table:
# Cov 35
M.15.25.F.15.25.MAR.cov.cl.35 <- quant.med(d.MAR.cov.35$cov.MAR.a.35.cl.M.15.25.F.15.25)
M.25.40.F.15.25.MAR.cov.cl.35 <- quant.med(d.MAR.cov.35$cov.MAR.a.35.cl.M.25.40.F.15.25)
M.40.50.F.15.25.MAR.cov.cl.35 <- quant.med(d.MAR.cov.35$cov.MAR.a.35.cl.M.40.50.F.15.25)
M.15.25.F.25.40.MAR.cov.cl.35 <- quant.med(d.MAR.cov.35$cov.MAR.a.35.cl.M.15.25.F.25.40)
M.25.40.F.25.40.MAR.cov.cl.35 <- quant.med(d.MAR.cov.35$cov.MAR.a.35.cl.M.25.40.F.25.40)
M.40.50.F.25.40.MAR.cov.cl.35 <- quant.med(d.MAR.cov.35$cov.MAR.a.35.cl.M.40.50.F.25.40)
M.15.25.F.40.50.MAR.cov.cl.35 <- quant.med(d.MAR.cov.35$cov.MAR.a.35.cl.M.15.25.F.40.50)
M.25.40.F.40.50.MAR.cov.cl.35 <- quant.med(d.MAR.cov.35$cov.MAR.a.35.cl.M.25.40.F.40.50)
M.40.50.F.40.50.MAR.cov.cl.35 <- quant.med(d.MAR.cov.35$cov.MAR.a.35.cl.M.40.50.F.40.50)
MAR.cov.35.cl.age.groups.table <- matrix(c((M.15.25.F.15.25.MAR.cov.cl.35[2]), (M.15.25.F.25.40.MAR.cov.cl.35[2]), (M.15.25.F.40.50.MAR.cov.cl.35[2]),
(M.25.40.F.15.25.MAR.cov.cl.35[2]), (M.25.40.F.25.40.MAR.cov.cl.35[2]), (M.25.40.F.40.50.MAR.cov.cl.35[2]),
(M.40.50.F.15.25.MAR.cov.cl.35[2]), (M.40.50.F.25.40.MAR.cov.cl.35[2]), (M.40.50.F.40.50.MAR.cov.cl.35[2])),
ncol = 3,
byrow = TRUE)
# colnames(MAR.cov.35.cl.age.groups.table) <- c("Female.15.25", "Female.25.40", "Female.40.50")
# rownames(MAR.cov.35.cl.age.groups.table) <- c("Male.15.25", "Male.25.40", "Male.40.50")
#
# Cov 40
M.15.25.F.15.25.MAR.cov.cl.40 <- quant.med(d.MAR.cov.40$cov.MAR.a.40.cl.M.15.25.F.15.25)
M.25.40.F.15.25.MAR.cov.cl.40 <- quant.med(d.MAR.cov.40$cov.MAR.a.40.cl.M.25.40.F.15.25)
M.40.50.F.15.25.MAR.cov.cl.40 <- quant.med(d.MAR.cov.40$cov.MAR.a.40.cl.M.40.50.F.15.25)
M.15.25.F.25.40.MAR.cov.cl.40 <- quant.med(d.MAR.cov.40$cov.MAR.a.40.cl.M.15.25.F.25.40)
M.25.40.F.25.40.MAR.cov.cl.40 <- quant.med(d.MAR.cov.40$cov.MAR.a.40.cl.M.25.40.F.25.40)
M.40.50.F.25.40.MAR.cov.cl.40 <- quant.med(d.MAR.cov.40$cov.MAR.a.40.cl.M.40.50.F.25.40)
M.15.25.F.40.50.MAR.cov.cl.40 <- quant.med(d.MAR.cov.40$cov.MAR.a.40.cl.M.15.25.F.40.50)
M.25.40.F.40.50.MAR.cov.cl.40 <- quant.med(d.MAR.cov.40$cov.MAR.a.40.cl.M.25.40.F.40.50)
M.40.50.F.40.50.MAR.cov.cl.40 <- quant.med(d.MAR.cov.40$cov.MAR.a.40.cl.M.40.50.F.40.50)
MAR.cov.40.cl.age.groups.table <- matrix(c((M.15.25.F.15.25.MAR.cov.cl.40[2]), (M.15.25.F.25.40.MAR.cov.cl.40[2]), (M.15.25.F.40.50.MAR.cov.cl.40[2]),
(M.25.40.F.15.25.MAR.cov.cl.40[2]), (M.25.40.F.25.40.MAR.cov.cl.40[2]), (M.25.40.F.40.50.MAR.cov.cl.40[2]),
(M.40.50.F.15.25.MAR.cov.cl.40[2]), (M.40.50.F.25.40.MAR.cov.cl.40[2]), (M.40.50.F.40.50.MAR.cov.cl.40[2])),
ncol = 3,
byrow = TRUE)
# colnames(MAR.cov.40.cl.age.groups.table) <- c("Female.15.25", "Female.25.40", "Female.40.50")
# rownames(MAR.cov.40.cl.age.groups.table) <- c("Male.15.25", "Male.25.40", "Male.40.50")
#
# Cov 45
M.15.25.F.15.25.MAR.cov.cl.45 <- quant.med(d.MAR.cov.45$cov.MAR.a.45.cl.M.15.25.F.15.25)
M.25.40.F.15.25.MAR.cov.cl.45 <- quant.med(d.MAR.cov.45$cov.MAR.a.45.cl.M.25.40.F.15.25)
M.40.50.F.15.25.MAR.cov.cl.45 <- quant.med(d.MAR.cov.45$cov.MAR.a.45.cl.M.40.50.F.15.25)
M.15.25.F.25.40.MAR.cov.cl.45 <- quant.med(d.MAR.cov.45$cov.MAR.a.45.cl.M.15.25.F.25.40)
M.25.40.F.25.40.MAR.cov.cl.45 <- quant.med(d.MAR.cov.45$cov.MAR.a.45.cl.M.25.40.F.25.40)
M.40.50.F.25.40.MAR.cov.cl.45 <- quant.med(d.MAR.cov.45$cov.MAR.a.45.cl.M.40.50.F.25.40)
M.15.25.F.40.50.MAR.cov.cl.45 <- quant.med(d.MAR.cov.45$cov.MAR.a.45.cl.M.15.25.F.40.50)
M.25.40.F.40.50.MAR.cov.cl.45 <- quant.med(d.MAR.cov.45$cov.MAR.a.45.cl.M.25.40.F.40.50)
M.40.50.F.40.50.MAR.cov.cl.45 <- quant.med(d.MAR.cov.45$cov.MAR.a.45.cl.M.40.50.F.40.50)
MAR.cov.45.cl.age.groups.table <- matrix(c((M.15.25.F.15.25.MAR.cov.cl.45[2]), (M.15.25.F.25.40.MAR.cov.cl.45[2]), (M.15.25.F.40.50.MAR.cov.cl.45[2]),
(M.25.40.F.15.25.MAR.cov.cl.45[2]), (M.25.40.F.25.40.MAR.cov.cl.45[2]), (M.25.40.F.40.50.MAR.cov.cl.45[2]),
(M.40.50.F.15.25.MAR.cov.cl.45[2]), (M.40.50.F.25.40.MAR.cov.cl.45[2]), (M.40.50.F.40.50.MAR.cov.cl.45[2])),
ncol = 3,
byrow = TRUE)
# colnames(MAR.cov.45.cl.age.groups.table) <- c("Female.15.25", "Female.25.40", "Female.40.50")
# rownames(MAR.cov.45.cl.age.groups.table) <- c("Male.15.25", "Male.25.40", "Male.40.50")
# Cov 50
M.15.25.F.15.25.MAR.cov.cl.50 <- quant.med(d.MAR.cov.50$cov.MAR.a.50.cl.M.15.25.F.15.25)
M.25.40.F.15.25.MAR.cov.cl.50 <- quant.med(d.MAR.cov.50$cov.MAR.a.50.cl.M.25.40.F.15.25)
M.40.50.F.15.25.MAR.cov.cl.50 <- quant.med(d.MAR.cov.50$cov.MAR.a.50.cl.M.40.50.F.15.25)
M.15.25.F.25.40.MAR.cov.cl.50 <- quant.med(d.MAR.cov.50$cov.MAR.a.50.cl.M.15.25.F.25.40)
M.25.40.F.25.40.MAR.cov.cl.50 <- quant.med(d.MAR.cov.50$cov.MAR.a.50.cl.M.25.40.F.25.40)
M.40.50.F.25.40.MAR.cov.cl.50 <- quant.med(d.MAR.cov.50$cov.MAR.a.50.cl.M.40.50.F.25.40)
M.15.25.F.40.50.MAR.cov.cl.50 <- quant.med(d.MAR.cov.50$cov.MAR.a.50.cl.M.15.25.F.40.50)
M.25.40.F.40.50.MAR.cov.cl.50 <- quant.med(d.MAR.cov.50$cov.MAR.a.50.cl.M.25.40.F.40.50)
M.40.50.F.40.50.MAR.cov.cl.50 <- quant.med(d.MAR.cov.50$cov.MAR.a.50.cl.M.40.50.F.40.50)
MAR.cov.50.cl.age.groups.table <- matrix(c((M.15.25.F.15.25.MAR.cov.cl.50[2]), (M.15.25.F.25.40.MAR.cov.cl.50[2]), (M.15.25.F.40.50.MAR.cov.cl.50[2]),
(M.25.40.F.15.25.MAR.cov.cl.50[2]), (M.25.40.F.25.40.MAR.cov.cl.50[2]), (M.25.40.F.40.50.MAR.cov.cl.50[2]),
(M.40.50.F.15.25.MAR.cov.cl.50[2]), (M.40.50.F.25.40.MAR.cov.cl.50[2]), (M.40.50.F.40.50.MAR.cov.cl.50[2])),
ncol = 3,
byrow = TRUE)
# colnames(MAR.cov.50.cl.age.groups.table) <- c("Female.15.25", "Female.25.40", "Female.40.50")
# rownames(MAR.cov.50.cl.age.groups.table) <- c("Male.15.25", "Male.25.40", "Male.40.50")
# Cov 55
M.15.25.F.15.25.MAR.cov.cl.55 <- quant.med(d.MAR.cov.55$cov.MAR.a.55.cl.M.15.25.F.15.25)
M.25.40.F.15.25.MAR.cov.cl.55 <- quant.med(d.MAR.cov.55$cov.MAR.a.55.cl.M.25.40.F.15.25)
M.40.50.F.15.25.MAR.cov.cl.55 <- quant.med(d.MAR.cov.55$cov.MAR.a.55.cl.M.40.50.F.15.25)
M.15.25.F.25.40.MAR.cov.cl.55 <- quant.med(d.MAR.cov.55$cov.MAR.a.55.cl.M.15.25.F.25.40)
M.25.40.F.25.40.MAR.cov.cl.55 <- quant.med(d.MAR.cov.55$cov.MAR.a.55.cl.M.25.40.F.25.40)
M.40.50.F.25.40.MAR.cov.cl.55 <- quant.med(d.MAR.cov.55$cov.MAR.a.55.cl.M.40.50.F.25.40)
M.15.25.F.40.50.MAR.cov.cl.55 <- quant.med(d.MAR.cov.55$cov.MAR.a.55.cl.M.15.25.F.40.50)
M.25.40.F.40.50.MAR.cov.cl.55 <- quant.med(d.MAR.cov.55$cov.MAR.a.55.cl.M.25.40.F.40.50)
M.40.50.F.40.50.MAR.cov.cl.55 <- quant.med(d.MAR.cov.55$cov.MAR.a.55.cl.M.40.50.F.40.50)
MAR.cov.55.cl.age.groups.table <- matrix(c((M.15.25.F.15.25.MAR.cov.cl.55[2]), (M.15.25.F.25.40.MAR.cov.cl.55[2]), (M.15.25.F.40.50.MAR.cov.cl.55[2]),
(M.25.40.F.15.25.MAR.cov.cl.55[2]), (M.25.40.F.25.40.MAR.cov.cl.55[2]), (M.25.40.F.40.50.MAR.cov.cl.55[2]),
(M.40.50.F.15.25.MAR.cov.cl.55[2]), (M.40.50.F.25.40.MAR.cov.cl.55[2]), (M.40.50.F.40.50.MAR.cov.cl.55[2])),
ncol = 3,
byrow = TRUE)
# colnames(MAR.cov.55.cl.age.groups.table) <- c("Female.15.25", "Female.25.40", "Female.40.50")
# rownames(MAR.cov.55.cl.age.groups.table) <- c("Male.15.25", "Male.25.40", "Male.40.50")
# Cov 60
M.15.25.F.15.25.MAR.cov.cl.60 <- quant.med(d.MAR.cov.60$cov.MAR.a.60.cl.M.15.25.F.15.25)
M.25.40.F.15.25.MAR.cov.cl.60 <- quant.med(d.MAR.cov.60$cov.MAR.a.60.cl.M.25.40.F.15.25)
M.40.50.F.15.25.MAR.cov.cl.60 <- quant.med(d.MAR.cov.60$cov.MAR.a.60.cl.M.40.50.F.15.25)
M.15.25.F.25.40.MAR.cov.cl.60 <- quant.med(d.MAR.cov.60$cov.MAR.a.60.cl.M.15.25.F.25.40)
M.25.40.F.25.40.MAR.cov.cl.60 <- quant.med(d.MAR.cov.60$cov.MAR.a.60.cl.M.25.40.F.25.40)
M.40.50.F.25.40.MAR.cov.cl.60 <- quant.med(d.MAR.cov.60$cov.MAR.a.60.cl.M.40.50.F.25.40)
M.15.25.F.40.50.MAR.cov.cl.60 <- quant.med(d.MAR.cov.60$cov.MAR.a.60.cl.M.15.25.F.40.50)
M.25.40.F.40.50.MAR.cov.cl.60 <- quant.med(d.MAR.cov.60$cov.MAR.a.60.cl.M.25.40.F.40.50)
M.40.50.F.40.50.MAR.cov.cl.60 <- quant.med(d.MAR.cov.60$cov.MAR.a.60.cl.M.40.50.F.40.50)
MAR.cov.60.cl.age.groups.table <- matrix(c((M.15.25.F.15.25.MAR.cov.cl.60[2]), (M.15.25.F.25.40.MAR.cov.cl.60[2]), (M.15.25.F.40.50.MAR.cov.cl.60[2]),
(M.25.40.F.15.25.MAR.cov.cl.60[2]), (M.25.40.F.25.40.MAR.cov.cl.60[2]), (M.25.40.F.40.50.MAR.cov.cl.60[2]),
(M.40.50.F.15.25.MAR.cov.cl.60[2]), (M.40.50.F.25.40.MAR.cov.cl.60[2]), (M.40.50.F.40.50.MAR.cov.cl.60[2])),
ncol = 3,
byrow = TRUE)
# colnames(MAR.cov.60.cl.age.groups.table) <- c("Female.15.25", "Female.25.40", "Female.40.50")
# rownames(MAR.cov.60.cl.age.groups.table) <- c("Male.15.25", "Male.25.40", "Male.40.50")
# Cov 65
M.15.25.F.15.25.MAR.cov.cl.65 <- quant.med(d.MAR.cov.65$cov.MAR.a.65.cl.M.15.25.F.15.25)
M.25.40.F.15.25.MAR.cov.cl.65 <- quant.med(d.MAR.cov.65$cov.MAR.a.65.cl.M.25.40.F.15.25)
M.40.50.F.15.25.MAR.cov.cl.65 <- quant.med(d.MAR.cov.65$cov.MAR.a.65.cl.M.40.50.F.15.25)
M.15.25.F.25.40.MAR.cov.cl.65 <- quant.med(d.MAR.cov.65$cov.MAR.a.65.cl.M.15.25.F.25.40)
M.25.40.F.25.40.MAR.cov.cl.65 <- quant.med(d.MAR.cov.65$cov.MAR.a.65.cl.M.25.40.F.25.40)
M.40.50.F.25.40.MAR.cov.cl.65 <- quant.med(d.MAR.cov.65$cov.MAR.a.65.cl.M.40.50.F.25.40)
M.15.25.F.40.50.MAR.cov.cl.65 <- quant.med(d.MAR.cov.65$cov.MAR.a.65.cl.M.15.25.F.40.50)
M.25.40.F.40.50.MAR.cov.cl.65 <- quant.med(d.MAR.cov.65$cov.MAR.a.65.cl.M.25.40.F.40.50)
M.40.50.F.40.50.MAR.cov.cl.65 <- quant.med(d.MAR.cov.65$cov.MAR.a.65.cl.M.40.50.F.40.50)
MAR.cov.65.cl.age.groups.table <- matrix(c((M.15.25.F.15.25.MAR.cov.cl.65[2]), (M.15.25.F.25.40.MAR.cov.cl.65[2]), (M.15.25.F.40.50.MAR.cov.cl.65[2]),
(M.25.40.F.15.25.MAR.cov.cl.65[2]), (M.25.40.F.25.40.MAR.cov.cl.65[2]), (M.25.40.F.40.50.MAR.cov.cl.65[2]),
(M.40.50.F.15.25.MAR.cov.cl.65[2]), (M.40.50.F.25.40.MAR.cov.cl.65[2]), (M.40.50.F.40.50.MAR.cov.cl.65[2])),
ncol = 3,
byrow = TRUE)
# colnames(MAR.cov.65.cl.age.groups.table) <- c("Female.15.25", "Female.25.40", "Female.40.50")
# rownames(MAR.cov.65.cl.age.groups.table) <- c("Male.15.25", "Male.25.40", "Male.40.50")
# Cov 70
M.15.25.F.15.25.MAR.cov.cl.70 <- quant.med(d.MAR.cov.70$cov.MAR.a.70.cl.M.15.25.F.15.25)
M.25.40.F.15.25.MAR.cov.cl.70 <- quant.med(d.MAR.cov.70$cov.MAR.a.70.cl.M.25.40.F.15.25)
M.40.50.F.15.25.MAR.cov.cl.70 <- quant.med(d.MAR.cov.70$cov.MAR.a.70.cl.M.40.50.F.15.25)
M.15.25.F.25.40.MAR.cov.cl.70 <- quant.med(d.MAR.cov.70$cov.MAR.a.70.cl.M.15.25.F.25.40)
M.25.40.F.25.40.MAR.cov.cl.70 <- quant.med(d.MAR.cov.70$cov.MAR.a.70.cl.M.25.40.F.25.40)
M.40.50.F.25.40.MAR.cov.cl.70 <- quant.med(d.MAR.cov.70$cov.MAR.a.70.cl.M.40.50.F.25.40)
M.15.25.F.40.50.MAR.cov.cl.70 <- quant.med(d.MAR.cov.70$cov.MAR.a.70.cl.M.15.25.F.40.50)
M.25.40.F.40.50.MAR.cov.cl.70 <- quant.med(d.MAR.cov.70$cov.MAR.a.70.cl.M.25.40.F.40.50)
M.40.50.F.40.50.MAR.cov.cl.70 <- quant.med(d.MAR.cov.70$cov.MAR.a.70.cl.M.40.50.F.40.50)
MAR.cov.70.cl.age.groups.table <- matrix(c((M.15.25.F.15.25.MAR.cov.cl.70[2]), (M.15.25.F.25.40.MAR.cov.cl.70[2]), (M.15.25.F.40.50.MAR.cov.cl.70[2]),
(M.25.40.F.15.25.MAR.cov.cl.70[2]), (M.25.40.F.25.40.MAR.cov.cl.70[2]), (M.25.40.F.40.50.MAR.cov.cl.70[2]),
(M.40.50.F.15.25.MAR.cov.cl.70[2]), (M.40.50.F.25.40.MAR.cov.cl.70[2]), (M.40.50.F.40.50.MAR.cov.cl.70[2])),
ncol = 3,
byrow = TRUE)
# colnames(MAR.cov.70.cl.age.groups.table) <- c("Female.15.25", "Female.25.40", "Female.40.50")
# rownames(MAR.cov.70.cl.age.groups.table) <- c("Male.15.25", "Male.25.40", "Male.40.50")
# Cov 75
M.15.25.F.15.25.MAR.cov.cl.75 <- quant.med(d.MAR.cov.75$cov.MAR.a.75.cl.M.15.25.F.15.25)
M.25.40.F.15.25.MAR.cov.cl.75 <- quant.med(d.MAR.cov.75$cov.MAR.a.75.cl.M.25.40.F.15.25)
M.40.50.F.15.25.MAR.cov.cl.75 <- quant.med(d.MAR.cov.75$cov.MAR.a.75.cl.M.40.50.F.15.25)
M.15.25.F.25.40.MAR.cov.cl.75 <- quant.med(d.MAR.cov.75$cov.MAR.a.75.cl.M.15.25.F.25.40)
M.25.40.F.25.40.MAR.cov.cl.75 <- quant.med(d.MAR.cov.75$cov.MAR.a.75.cl.M.25.40.F.25.40)
M.40.50.F.25.40.MAR.cov.cl.75 <- quant.med(d.MAR.cov.75$cov.MAR.a.75.cl.M.40.50.F.25.40)
M.15.25.F.40.50.MAR.cov.cl.75 <- quant.med(d.MAR.cov.75$cov.MAR.a.75.cl.M.15.25.F.40.50)
M.25.40.F.40.50.MAR.cov.cl.75 <- quant.med(d.MAR.cov.75$cov.MAR.a.75.cl.M.25.40.F.40.50)
M.40.50.F.40.50.MAR.cov.cl.75 <- quant.med(d.MAR.cov.75$cov.MAR.a.75.cl.M.40.50.F.40.50)
MAR.cov.75.cl.age.groups.table <- matrix(c((M.15.25.F.15.25.MAR.cov.cl.75[2]), (M.15.25.F.25.40.MAR.cov.cl.75[2]), (M.15.25.F.40.50.MAR.cov.cl.75[2]),
(M.25.40.F.15.25.MAR.cov.cl.75[2]), (M.25.40.F.25.40.MAR.cov.cl.75[2]), (M.25.40.F.40.50.MAR.cov.cl.75[2]),
(M.40.50.F.15.25.MAR.cov.cl.75[2]), (M.40.50.F.25.40.MAR.cov.cl.75[2]), (M.40.50.F.40.50.MAR.cov.cl.75[2])),
ncol = 3,
byrow = TRUE)
# colnames(MAR.cov.75.cl.age.groups.table) <- c("Female.15.25", "Female.25.40", "Female.40.50")
# rownames(MAR.cov.75.cl.age.groups.table) <- c("Male.15.25", "Male.25.40", "Male.40.50")
# Cov 80
M.15.25.F.15.25.MAR.cov.cl.80 <- quant.med(d.MAR.cov.80$cov.MAR.a.80.cl.M.15.25.F.15.25)
M.25.40.F.15.25.MAR.cov.cl.80 <- quant.med(d.MAR.cov.80$cov.MAR.a.80.cl.M.25.40.F.15.25)
M.40.50.F.15.25.MAR.cov.cl.80 <- quant.med(d.MAR.cov.80$cov.MAR.a.80.cl.M.40.50.F.15.25)
M.15.25.F.25.40.MAR.cov.cl.80 <- quant.med(d.MAR.cov.80$cov.MAR.a.80.cl.M.15.25.F.25.40)
M.25.40.F.25.40.MAR.cov.cl.80 <- quant.med(d.MAR.cov.80$cov.MAR.a.80.cl.M.25.40.F.25.40)
M.40.50.F.25.40.MAR.cov.cl.80 <- quant.med(d.MAR.cov.80$cov.MAR.a.80.cl.M.40.50.F.25.40)
M.15.25.F.40.50.MAR.cov.cl.80 <- quant.med(d.MAR.cov.80$cov.MAR.a.80.cl.M.15.25.F.40.50)
M.25.40.F.40.50.MAR.cov.cl.80 <- quant.med(d.MAR.cov.80$cov.MAR.a.80.cl.M.25.40.F.40.50)
M.40.50.F.40.50.MAR.cov.cl.80 <- quant.med(d.MAR.cov.80$cov.MAR.a.80.cl.M.40.50.F.40.50)
MAR.cov.80.cl.age.groups.table <- matrix(c((M.15.25.F.15.25.MAR.cov.cl.80[2]), (M.15.25.F.25.40.MAR.cov.cl.80[2]), (M.15.25.F.40.50.MAR.cov.cl.80[2]),
(M.25.40.F.15.25.MAR.cov.cl.80[2]), (M.25.40.F.25.40.MAR.cov.cl.80[2]), (M.25.40.F.40.50.MAR.cov.cl.80[2]),
(M.40.50.F.15.25.MAR.cov.cl.80[2]), (M.40.50.F.25.40.MAR.cov.cl.80[2]), (M.40.50.F.40.50.MAR.cov.cl.80[2])),
ncol = 3,
byrow = TRUE)
# colnames(MAR.cov.80.cl.age.groups.table) <- c("Female.15.25", "Female.25.40", "Female.40.50")
# rownames(MAR.cov.80.cl.age.groups.table) <- c("Male.15.25", "Male.25.40", "Male.40.50")
# Cov 85
M.15.25.F.15.25.MAR.cov.cl.85 <- quant.med(d.MAR.cov.85$cov.MAR.a.85.cl.M.15.25.F.15.25)
M.25.40.F.15.25.MAR.cov.cl.85 <- quant.med(d.MAR.cov.85$cov.MAR.a.85.cl.M.25.40.F.15.25)
M.40.50.F.15.25.MAR.cov.cl.85 <- quant.med(d.MAR.cov.85$cov.MAR.a.85.cl.M.40.50.F.15.25)
M.15.25.F.25.40.MAR.cov.cl.85 <- quant.med(d.MAR.cov.85$cov.MAR.a.85.cl.M.15.25.F.25.40)
M.25.40.F.25.40.MAR.cov.cl.85 <- quant.med(d.MAR.cov.85$cov.MAR.a.85.cl.M.25.40.F.25.40)
M.40.50.F.25.40.MAR.cov.cl.85 <- quant.med(d.MAR.cov.85$cov.MAR.a.85.cl.M.40.50.F.25.40)
M.15.25.F.40.50.MAR.cov.cl.85 <- quant.med(d.MAR.cov.85$cov.MAR.a.85.cl.M.15.25.F.40.50)
M.25.40.F.40.50.MAR.cov.cl.85 <- quant.med(d.MAR.cov.85$cov.MAR.a.85.cl.M.25.40.F.40.50)
M.40.50.F.40.50.MAR.cov.cl.85 <- quant.med(d.MAR.cov.85$cov.MAR.a.85.cl.M.40.50.F.40.50)
MAR.cov.85.cl.age.groups.table <- matrix(c((M.15.25.F.15.25.MAR.cov.cl.85[2]), (M.15.25.F.25.40.MAR.cov.cl.85[2]), (M.15.25.F.40.50.MAR.cov.cl.85[2]),
(M.25.40.F.15.25.MAR.cov.cl.85[2]), (M.25.40.F.25.40.MAR.cov.cl.85[2]), (M.25.40.F.40.50.MAR.cov.cl.85[2]),
(M.40.50.F.15.25.MAR.cov.cl.85[2]), (M.40.50.F.25.40.MAR.cov.cl.85[2]), (M.40.50.F.40.50.MAR.cov.cl.85[2])),
ncol = 3,
byrow = TRUE)
# colnames(MAR.cov.85.cl.age.groups.table) <- c("Female.15.25", "Female.25.40", "Female.40.50")
# rownames(MAR.cov.85.cl.age.groups.table) <- c("Male.15.25", "Male.25.40", "Male.40.50")
# Cov 90
M.15.25.F.15.25.MAR.cov.cl.90 <- quant.med(d.MAR.cov.90$cov.MAR.a.90.cl.M.15.25.F.15.25)
M.25.40.F.15.25.MAR.cov.cl.90 <- quant.med(d.MAR.cov.90$cov.MAR.a.90.cl.M.25.40.F.15.25)
M.40.50.F.15.25.MAR.cov.cl.90 <- quant.med(d.MAR.cov.90$cov.MAR.a.90.cl.M.40.50.F.15.25)
M.15.25.F.25.40.MAR.cov.cl.90 <- quant.med(d.MAR.cov.90$cov.MAR.a.90.cl.M.15.25.F.25.40)
M.25.40.F.25.40.MAR.cov.cl.90 <- quant.med(d.MAR.cov.90$cov.MAR.a.90.cl.M.25.40.F.25.40)
M.40.50.F.25.40.MAR.cov.cl.90 <- quant.med(d.MAR.cov.90$cov.MAR.a.90.cl.M.40.50.F.25.40)
M.15.25.F.40.50.MAR.cov.cl.90 <- quant.med(d.MAR.cov.90$cov.MAR.a.90.cl.M.15.25.F.40.50)
M.25.40.F.40.50.MAR.cov.cl.90 <- quant.med(d.MAR.cov.90$cov.MAR.a.90.cl.M.25.40.F.40.50)
M.40.50.F.40.50.MAR.cov.cl.90 <- quant.med(d.MAR.cov.90$cov.MAR.a.90.cl.M.40.50.F.40.50)
MAR.cov.90.cl.age.groups.table <- matrix(c((M.15.25.F.15.25.MAR.cov.cl.90[2]), (M.15.25.F.25.40.MAR.cov.cl.90[2]), (M.15.25.F.40.50.MAR.cov.cl.90[2]),
(M.25.40.F.15.25.MAR.cov.cl.90[2]), (M.25.40.F.25.40.MAR.cov.cl.90[2]), (M.25.40.F.40.50.MAR.cov.cl.90[2]),
(M.40.50.F.15.25.MAR.cov.cl.90[2]), (M.40.50.F.25.40.MAR.cov.cl.90[2]), (M.40.50.F.40.50.MAR.cov.cl.90[2])),
ncol = 3,
byrow = TRUE)
# colnames(MAR.cov.90.cl.age.groups.table) <- c("Female.15.25", "Female.25.40", "Female.40.50")
# rownames(MAR.cov.90.cl.age.groups.table) <- c("Male.15.25", "Male.25.40", "Male.40.50")
# Cov 95
M.15.25.F.15.25.MAR.cov.cl.95 <- quant.med(d.MAR.cov.95$cov.MAR.a.95.cl.M.15.25.F.15.25)
M.25.40.F.15.25.MAR.cov.cl.95 <- quant.med(d.MAR.cov.95$cov.MAR.a.95.cl.M.25.40.F.15.25)
M.40.50.F.15.25.MAR.cov.cl.95 <- quant.med(d.MAR.cov.95$cov.MAR.a.95.cl.M.40.50.F.15.25)
M.15.25.F.25.40.MAR.cov.cl.95 <- quant.med(d.MAR.cov.95$cov.MAR.a.95.cl.M.15.25.F.25.40)
M.25.40.F.25.40.MAR.cov.cl.95 <- quant.med(d.MAR.cov.95$cov.MAR.a.95.cl.M.25.40.F.25.40)
M.40.50.F.25.40.MAR.cov.cl.95 <- quant.med(d.MAR.cov.95$cov.MAR.a.95.cl.M.40.50.F.25.40)
M.15.25.F.40.50.MAR.cov.cl.95 <- quant.med(d.MAR.cov.95$cov.MAR.a.95.cl.M.15.25.F.40.50)
M.25.40.F.40.50.MAR.cov.cl.95 <- quant.med(d.MAR.cov.95$cov.MAR.a.95.cl.M.25.40.F.40.50)
M.40.50.F.40.50.MAR.cov.cl.95 <- quant.med(d.MAR.cov.95$cov.MAR.a.95.cl.M.40.50.F.40.50)
MAR.cov.95.cl.age.groups.table <- matrix(c((M.15.25.F.15.25.MAR.cov.cl.95[2]), (M.15.25.F.25.40.MAR.cov.cl.95[2]), (M.15.25.F.40.50.MAR.cov.cl.95[2]),
(M.25.40.F.15.25.MAR.cov.cl.95[2]), (M.25.40.F.25.40.MAR.cov.cl.95[2]), (M.25.40.F.40.50.MAR.cov.cl.95[2]),
(M.40.50.F.15.25.MAR.cov.cl.95[2]), (M.40.50.F.25.40.MAR.cov.cl.95[2]), (M.40.50.F.40.50.MAR.cov.cl.95[2])),
ncol = 3,
byrow = TRUE)
# colnames(MAR.cov.95.cl.age.groups.table) <- c("Female.15.25", "Female.25.40", "Female.40.50")
# rownames(MAR.cov.95.cl.age.groups.table) <- c("Male.15.25", "Male.25.40", "Male.40.50")
#
# Agregated table of pairings in transmission clusters
pairing_clust_inf_scenarios <- matrix(c(M.15.25.F.15.25.MAR.cov.cl.35[2], M.15.25.F.15.25.MAR.cov.cl.40[2],
M.15.25.F.15.25.MAR.cov.cl.45[2], M.15.25.F.15.25.MAR.cov.cl.50[2],
M.15.25.F.15.25.MAR.cov.cl.55[2], M.15.25.F.15.25.MAR.cov.cl.60[2],
M.15.25.F.15.25.MAR.cov.cl.65[2], M.15.25.F.15.25.MAR.cov.cl.70[2],
M.15.25.F.15.25.MAR.cov.cl.75[2], M.15.25.F.15.25.MAR.cov.cl.80[2],
M.15.25.F.15.25.MAR.cov.cl.85[2], M.15.25.F.15.25.MAR.cov.cl.90[2],
M.15.25.F.15.25.MAR.cov.cl.95[2], M.15.25.F.15.25.cov.100[2],
M.25.40.F.15.25.MAR.cov.cl.35[2], M.25.40.F.15.25.MAR.cov.cl.40[2],
M.25.40.F.15.25.MAR.cov.cl.45[2], M.25.40.F.15.25.MAR.cov.cl.50[2],
M.25.40.F.15.25.MAR.cov.cl.55[2], M.25.40.F.15.25.MAR.cov.cl.60[2],
M.25.40.F.15.25.MAR.cov.cl.65[2], M.25.40.F.15.25.MAR.cov.cl.70[2],
M.25.40.F.15.25.MAR.cov.cl.75[2], M.25.40.F.15.25.MAR.cov.cl.80[2],
M.25.40.F.15.25.MAR.cov.cl.85[2], M.25.40.F.15.25.MAR.cov.cl.90[2],
M.25.40.F.15.25.MAR.cov.cl.95[2], M.25.40.F.15.25.cov.100[2],
M.40.50.F.15.25.MAR.cov.cl.35[2], M.40.50.F.15.25.MAR.cov.cl.40[2],
M.40.50.F.15.25.MAR.cov.cl.45[2], M.40.50.F.15.25.MAR.cov.cl.50[2],
M.40.50.F.15.25.MAR.cov.cl.55[2], M.40.50.F.15.25.MAR.cov.cl.60[2],
M.40.50.F.15.25.MAR.cov.cl.65[2], M.40.50.F.15.25.MAR.cov.cl.70[2],
M.40.50.F.15.25.MAR.cov.cl.75[2], M.40.50.F.15.25.MAR.cov.cl.80[2],
M.40.50.F.15.25.MAR.cov.cl.85[2], M.40.50.F.15.25.MAR.cov.cl.90[2],
M.40.50.F.15.25.MAR.cov.cl.95[2], M.40.50.F.15.25.cov.100[2],
M.15.25.F.25.40.MAR.cov.cl.35[2], M.15.25.F.25.40.MAR.cov.cl.40[2],
M.15.25.F.25.40.MAR.cov.cl.45[2], M.15.25.F.25.40.MAR.cov.cl.50[2],
M.15.25.F.25.40.MAR.cov.cl.55[2], M.15.25.F.25.40.MAR.cov.cl.60[2],
M.15.25.F.25.40.MAR.cov.cl.65[2], M.15.25.F.25.40.MAR.cov.cl.70[2],
M.15.25.F.25.40.MAR.cov.cl.75[2], M.15.25.F.25.40.MAR.cov.cl.80[2],
M.15.25.F.25.40.MAR.cov.cl.85[2], M.15.25.F.25.40.MAR.cov.cl.90[2],
M.15.25.F.25.40.MAR.cov.cl.95[2], M.15.25.F.25.40.cov.100[2],
M.25.40.F.25.40.MAR.cov.cl.35[2], M.25.40.F.25.40.MAR.cov.cl.40[2],
M.25.40.F.25.40.MAR.cov.cl.45[2], M.25.40.F.25.40.MAR.cov.cl.50[2],
M.25.40.F.25.40.MAR.cov.cl.55[2], M.25.40.F.25.40.MAR.cov.cl.60[2],
M.25.40.F.25.40.MAR.cov.cl.65[2], M.25.40.F.25.40.MAR.cov.cl.70[2],
M.25.40.F.25.40.MAR.cov.cl.75[2], M.25.40.F.25.40.MAR.cov.cl.80[2],
M.25.40.F.25.40.MAR.cov.cl.85[2], M.25.40.F.25.40.MAR.cov.cl.90[2],
M.25.40.F.25.40.MAR.cov.cl.95[2], M.25.40.F.25.40.cov.100[2],
M.40.50.F.25.40.MAR.cov.cl.35[2], M.40.50.F.25.40.MAR.cov.cl.40[2],
M.40.50.F.25.40.MAR.cov.cl.45[2], M.40.50.F.25.40.MAR.cov.cl.50[2],
M.40.50.F.25.40.MAR.cov.cl.55[2], M.40.50.F.25.40.MAR.cov.cl.60[2],
M.40.50.F.25.40.MAR.cov.cl.65[2], M.40.50.F.25.40.MAR.cov.cl.70[2],
M.40.50.F.25.40.MAR.cov.cl.75[2], M.40.50.F.25.40.MAR.cov.cl.80[2],
M.40.50.F.25.40.MAR.cov.cl.85[2], M.40.50.F.25.40.MAR.cov.cl.90[2],
M.40.50.F.25.40.MAR.cov.cl.95[2], M.40.50.F.25.40.cov.100[2],
M.15.25.F.40.50.MAR.cov.cl.35[2], M.15.25.F.40.50.MAR.cov.cl.40[2],
M.15.25.F.40.50.MAR.cov.cl.45[2], M.15.25.F.40.50.MAR.cov.cl.50[2],
M.15.25.F.40.50.MAR.cov.cl.55[2], M.15.25.F.40.50.MAR.cov.cl.60[2],
M.15.25.F.40.50.MAR.cov.cl.65[2], M.15.25.F.40.50.MAR.cov.cl.70[2],
M.15.25.F.40.50.MAR.cov.cl.75[2], M.15.25.F.40.50.MAR.cov.cl.80[2],
M.15.25.F.40.50.MAR.cov.cl.85[2], M.15.25.F.40.50.MAR.cov.cl.90[2],
M.15.25.F.40.50.MAR.cov.cl.95[2], M.15.25.F.40.50.cov.100[2],
M.25.40.F.40.50.MAR.cov.cl.35[2], M.25.40.F.40.50.MAR.cov.cl.40[2],
M.25.40.F.40.50.MAR.cov.cl.45[2], M.25.40.F.40.50.MAR.cov.cl.50[2],
M.25.40.F.40.50.MAR.cov.cl.55[2], M.25.40.F.40.50.MAR.cov.cl.60[2],
M.25.40.F.40.50.MAR.cov.cl.65[2], M.25.40.F.40.50.MAR.cov.cl.70[2],
M.25.40.F.40.50.MAR.cov.cl.75[2], M.25.40.F.40.50.MAR.cov.cl.80[2],
M.25.40.F.40.50.MAR.cov.cl.85[2], M.25.40.F.40.50.MAR.cov.cl.90[2],
M.25.40.F.40.50.MAR.cov.cl.95[2], M.25.40.F.40.50.cov.100[2],
M.40.50.F.40.50.MAR.cov.cl.35[2], M.40.50.F.40.50.MAR.cov.cl.40[2],
M.40.50.F.40.50.MAR.cov.cl.45[2], M.40.50.F.40.50.MAR.cov.cl.50[2],
M.40.50.F.40.50.MAR.cov.cl.55[2], M.40.50.F.40.50.MAR.cov.cl.60[2],
M.40.50.F.40.50.MAR.cov.cl.65[2], M.40.50.F.40.50.MAR.cov.cl.70[2],
M.40.50.F.40.50.MAR.cov.cl.75[2], M.40.50.F.40.50.MAR.cov.cl.80[2],
M.40.50.F.40.50.MAR.cov.cl.85[2], M.40.50.F.40.50.MAR.cov.cl.90[2],
M.40.50.F.40.50.MAR.cov.cl.95[2], M.40.50.F.40.50.cov.100[2]),
ncol = 14,
byrow = TRUE)
colnames(pairing_clust_inf_scenarios) <- c("35", "40", "45",
"50", "55", "60",
"65", "70", "75",
"80", "85", "90",
"95", "true_100")
rownames(pairing_clust_inf_scenarios) <- c("M.15.25.F.15.25", "M.25.40.F.15.25", "M.40.50.F.15.25",
"M.15.25.F.25.40", "M.25.40.F.25.40", "M.40.50.F.25.40",
"M.15.25.F.40.50", "M.25.40.F.40.50", "M.40.50.F.40.50")
#
#
pairing_clust_inf_scenarios %>%
kable() %>%
kable_styling("striped") # OK| 35 | 40 | 45 | 50 | 55 | 60 | 65 | 70 | 75 | 80 | 85 | 90 | 95 | true_100 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| M.15.25.F.15.25 | 1 | 2 | 2 | 3 | 3.5 | 4 | 4 | 5 | 6 | 6 | 6 | 7 | 9 | 7 |
| M.25.40.F.15.25 | 2 | 2 | 3 | 4 | 5.0 | 6 | 6 | 8 | 10 | 12 | 13 | 16 | 18 | 33 |
| M.40.50.F.15.25 | 0 | 0 | 1 | 1 | 1.0 | 2 | 2 | 2 | 3 | 4 | 4 | 4 | 6 | 17 |
| M.15.25.F.25.40 | 0 | 0 | 0 | 0 | 0.0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| M.25.40.F.25.40 | 0 | 0 | 0 | 0 | 1.0 | 1 | 1 | 1 | 1 | 1 | 2 | 2 | 2 | 7 |
| M.40.50.F.25.40 | 0 | 0 | 1 | 1 | 1.0 | 1 | 2 | 2 | 2 | 2 | 3 | 3 | 3 | 15 |
| M.15.25.F.40.50 | 0 | 0 | 0 | 0 | 0.0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| M.25.40.F.40.50 | 0 | 0 | 0 | 0 | 0.0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| M.40.50.F.40.50 | 0 | 0 | 0 | 0 | 0.0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
write.csv(pairing_clust_inf_scenarios, file = "/home/david/age_mixing_patterns_phylogenetic/results/MAR_a/Table_a_12_Inf_Pairings_at_35_95_Coverage.csv")4 Proportions of pairings across age groups
With transmission clusters and pairings we can be able to compute the proportions of men/women from a given age group who are in within any transmission cluster. This means, for example if we have a transmission cluster with M men and W women for example, knowing also their age, we can place these men and women in the age groups (< 25 year, 25 - 40 years, and 40 - 50 years), and thereafter compute their proportions: number of men in a given age group who are in pair with women in another given age group.
4.1 True proportions at 100% sampling (sequence) coverage
Within 35 - 40 simulation, hen we consider 100% sampling (sequence) coverage, the true proprotions of men/women are given in the following table:
dr.cov.100 <- dr %>%
select(contains(".100"))
d.MAR.cov.100.prop.men <- dr.cov.100 %>%
select(contains("true.prop.men")) # true proportion of pairings inferred
d.MAR.cov.100.prop.women <- dr.cov.100 %>%
select(contains("true.prop.women"))
vector.MAR.true.cov.100.prop.men15.25.F.15.25 <- d.MAR.cov.100.prop.men[,1]
vector.MAR.true.cov.100.prop.women15.25.M.15.25 <- d.MAR.cov.100.prop.women[,1]
vector.MAR.true.cov.100.prop.men25.40.F.15.25 <- d.MAR.cov.100.prop.men[,2]
vector.MAR.true.cov.100.prop.women25.40.M.15.25 <- d.MAR.cov.100.prop.women[,2]
vector.MAR.true.cov.100.prop.men40.50.F.15.25 <- d.MAR.cov.100.prop.men[,3]
vector.MAR.true.cov.100.prop.women40.50.M.15.25 <- d.MAR.cov.100.prop.women[,3]
vector.MAR.true.cov.100.prop.men15.25.F.25.40 <- d.MAR.cov.100.prop.men[,4]
vector.MAR.true.cov.100.prop.women15.25.M.25.40 <- d.MAR.cov.100.prop.women[,4]
vector.MAR.true.cov.100.prop.men25.40.F.25.40 <- d.MAR.cov.100.prop.men[,5]
vector.MAR.true.cov.100.prop.women25.40.M.25.40 <- d.MAR.cov.100.prop.women[,5]
vector.MAR.true.cov.100.prop.men40.50.F.25.40 <- d.MAR.cov.100.prop.men[,6]
vector.MAR.true.cov.100.prop.women40.50.M.25.40 <- d.MAR.cov.100.prop.women[,6]
vector.MAR.true.cov.100.prop.men15.25.F.40.50 <- d.MAR.cov.100.prop.men[,7]
vector.MAR.true.cov.100.prop.women15.25.M.40.50 <- d.MAR.cov.100.prop.women[,7]
vector.MAR.true.cov.100.prop.men25.40.F.40.50 <- d.MAR.cov.100.prop.men[,8]
vector.MAR.true.cov.100.prop.women25.40.M.40.50 <- d.MAR.cov.100.prop.women[,8]
vector.MAR.true.cov.100.prop.men40.50.F.40.50 <- d.MAR.cov.100.prop.men[,9]
vector.MAR.true.cov.100.prop.women40.50.M.40.50 <- d.MAR.cov.100.prop.women[,9]
# Summarrised
d.MAR.true.cov.100.prop.men15.25.F.15.25 <- quant.med(d.MAR.cov.100.prop.men[,1])
d.MAR.true.cov.100.prop.women15.25.M.15.25 <- quant.med(d.MAR.cov.100.prop.women[,1])
d.MAR.true.cov.100.prop.men25.40.F.15.25 <- quant.med(d.MAR.cov.100.prop.men[,2])
d.MAR.true.cov.100.prop.women25.40.M.15.25 <- quant.med(d.MAR.cov.100.prop.women[,2])
d.MAR.true.cov.100.prop.men40.50.F.15.25 <- quant.med(d.MAR.cov.100.prop.men[,3])
d.MAR.true.cov.100.prop.women40.50.M.15.25 <- quant.med(d.MAR.cov.100.prop.women[,3])
d.MAR.true.cov.100.prop.men15.25.F.25.40 <- quant.med(d.MAR.cov.100.prop.men[,4])
d.MAR.true.cov.100.prop.women15.25.M.25.40 <- quant.med(d.MAR.cov.100.prop.women[,4])
d.MAR.true.cov.100.prop.men25.40.F.25.40 <- quant.med(d.MAR.cov.100.prop.men[,5])
d.MAR.true.cov.100.prop.women25.40.M.25.40 <- quant.med(d.MAR.cov.100.prop.women[,5])
d.MAR.true.cov.100.prop.men40.50.F.25.40 <- quant.med(d.MAR.cov.100.prop.men[,6])
d.MAR.true.cov.100.prop.women40.50.M.25.40 <- quant.med(d.MAR.cov.100.prop.women[,6])
d.MAR.true.cov.100.prop.men15.25.F.40.50 <- quant.med(d.MAR.cov.100.prop.men[,7])
d.MAR.true.cov.100.prop.women15.25.M.40.50 <- quant.med(d.MAR.cov.100.prop.women[,7])
d.MAR.true.cov.100.prop.men25.40.F.40.50 <- quant.med(d.MAR.cov.100.prop.men[,8])
d.MAR.true.cov.100.prop.women25.40.M.40.50 <- quant.med(d.MAR.cov.100.prop.women[,8])
d.MAR.true.cov.100.prop.men40.50.F.40.50 <- quant.med(d.MAR.cov.100.prop.men[,9])
d.MAR.true.cov.100.prop.women40.50.M.40.50 <- quant.med(d.MAR.cov.100.prop.women[,9])
props.val.F <- c(d.MAR.true.cov.100.prop.men15.25.F.15.25[2], d.MAR.true.cov.100.prop.women15.25.M.15.25[2],
d.MAR.true.cov.100.prop.men25.40.F.15.25[2], d.MAR.true.cov.100.prop.women25.40.M.15.25[2],
d.MAR.true.cov.100.prop.men40.50.F.15.25[2], d.MAR.true.cov.100.prop.women40.50.M.15.25[2],
d.MAR.true.cov.100.prop.men15.25.F.25.40[2], d.MAR.true.cov.100.prop.women15.25.M.25.40[2],
d.MAR.true.cov.100.prop.men25.40.F.25.40[2], d.MAR.true.cov.100.prop.women25.40.M.25.40[2],
d.MAR.true.cov.100.prop.men40.50.F.25.40[2], d.MAR.true.cov.100.prop.women40.50.M.25.40[2],
d.MAR.true.cov.100.prop.men15.25.F.40.50[2], d.MAR.true.cov.100.prop.women15.25.M.40.50[2],
d.MAR.true.cov.100.prop.men25.40.F.40.50[2], d.MAR.true.cov.100.prop.women25.40.M.40.50[2],
d.MAR.true.cov.100.prop.men40.50.F.40.50[2], d.MAR.true.cov.100.prop.women40.50.M.40.50[2])
props.val.U <- c(d.MAR.true.cov.100.prop.men15.25.F.15.25[3], d.MAR.true.cov.100.prop.women15.25.M.15.25[3],
d.MAR.true.cov.100.prop.men25.40.F.15.25[3], d.MAR.true.cov.100.prop.women25.40.M.15.25[3],
d.MAR.true.cov.100.prop.men40.50.F.15.25[3], d.MAR.true.cov.100.prop.women40.50.M.15.25[3],
d.MAR.true.cov.100.prop.men15.25.F.25.40[3], d.MAR.true.cov.100.prop.women15.25.M.25.40[3],
d.MAR.true.cov.100.prop.men25.40.F.25.40[3], d.MAR.true.cov.100.prop.women25.40.M.25.40[3],
d.MAR.true.cov.100.prop.men40.50.F.25.40[3], d.MAR.true.cov.100.prop.women40.50.M.25.40[3],
d.MAR.true.cov.100.prop.men15.25.F.40.50[3], d.MAR.true.cov.100.prop.women15.25.M.40.50[3],
d.MAR.true.cov.100.prop.men25.40.F.40.50[3], d.MAR.true.cov.100.prop.women25.40.M.40.50[3],
d.MAR.true.cov.100.prop.men40.50.F.40.50[3], d.MAR.true.cov.100.prop.women40.50.M.40.50[3])
props.val.L <- c(d.MAR.true.cov.100.prop.men15.25.F.15.25[1], d.MAR.true.cov.100.prop.women15.25.M.15.25[1],
d.MAR.true.cov.100.prop.men25.40.F.15.25[1], d.MAR.true.cov.100.prop.women25.40.M.15.25[1],
d.MAR.true.cov.100.prop.men40.50.F.15.25[1], d.MAR.true.cov.100.prop.women40.50.M.15.25[1],
d.MAR.true.cov.100.prop.men15.25.F.25.40[1], d.MAR.true.cov.100.prop.women15.25.M.25.40[1],
d.MAR.true.cov.100.prop.men25.40.F.25.40[1], d.MAR.true.cov.100.prop.women25.40.M.25.40[1],
d.MAR.true.cov.100.prop.men40.50.F.25.40[1], d.MAR.true.cov.100.prop.women40.50.M.25.40[1],
d.MAR.true.cov.100.prop.men15.25.F.40.50[1], d.MAR.true.cov.100.prop.women15.25.M.40.50[1],
d.MAR.true.cov.100.prop.men25.40.F.40.50[1], d.MAR.true.cov.100.prop.women25.40.M.40.50[1],
d.MAR.true.cov.100.prop.men40.50.F.40.50[1], d.MAR.true.cov.100.prop.women40.50.M.40.50[1])
names.props <- c("M.15.25.F.15.25", "F.15.25.M.15.25", "M.25.40.F.15.25", "F.25.40.M.15.25",
"M.40.50.F.15.25", "F.40.50.M.15.25", "M.15.25.F.25.40", "F.15.25.M.25.40",
"M.25.40.F.25.40", "F.25.40.M.25.40", "M.40.50.F.25.40", "F.40.50.M.25.40",
"M.15.25.F.40.50", "F.15.25.M.40.50", "M.25.40.F.40.50", "F.25.40.M.40.50",
"M.40.50.F.40.50", "F.40.50.M.40.50")
prop_pairings_100 <- data.frame(names.props, props.val.L, props.val.F, props.val.U)
colnames(prop_pairings_100) <- c("name", "lower.Q1", "med", "upper.Q3")
# prop_pairings_100 %>%
# kable() %>%
# kable_styling("striped") # Commented in OCTOBER
# For problematic age groups
prop_pairings_100_target <- prop_pairings_100[-c(4, 6, 7, 12, 13, 15, 17, 18),]
prop_pairings_100_target %>%
kable() %>%
kable_styling("striped")| name | lower.Q1 | med | upper.Q3 | |
|---|---|---|---|---|
| 1 | M.15.25.F.15.25 | 0.8888889 | 1.0000000 | 1.0000000 |
| 2 | F.15.25.M.15.25 | 0.0810811 | 0.1390374 | 0.2038927 |
| 3 | M.25.40.F.15.25 | 0.7619048 | 0.8260870 | 0.8780488 |
| 5 | M.40.50.F.15.25 | 0.4152299 | 0.5185185 | 0.6153846 |
| 8 | F.15.25.M.25.40 | 0.4708014 | 0.5562914 | 0.6361643 |
| 9 | M.25.40.F.25.40 | 0.1219512 | 0.1739130 | 0.2380952 |
| 10 | F.25.40.M.25.40 | 0.1818182 | 0.2800000 | 0.4000000 |
| 11 | M.40.50.F.25.40 | 0.3823529 | 0.4782609 | 0.5773525 |
| 14 | F.15.25.M.40.50 | 0.1945377 | 0.2779292 | 0.3780520 |
| 16 | F.25.40.M.40.50 | 0.5555556 | 0.6956522 | 0.8000000 |
#
write.csv(prop_pairings_100_target, file = "/home/david/age_mixing_patterns_phylogenetic/results/MAR_a/Table_a_13_True_Proportion_of_Pairings_at_100_Coverage.csv")
d <- as.data.frame(prop_pairings_100_target)
rownames(d) <- d$name
d <- d[order(row.names(d)), ]
d_f <- d
d_f$age_groups <- c(rep(c("15_24 & 15_24", "15_24 & 25_39", "15_24 & 40_49", "25_39 & 25_39", "25_39 & 40_49"), 2))
x <- c(rep(c("15_24 & 15_24", "15_24 & 25_39", "15_24 & 40_49", "25_39 & 25_39", "25_39 & 40_49"), 2))
d_f$x <- x
d_f$f_m <- c(rep("Females_Males", 5), rep("Males_Females", 5))
plots.prop_pairings_100_target <- ggplot(d_f, aes(x=x, y=med, colour=age_groups)) +
geom_errorbar(aes(ymin=lower.Q1, ymax=upper.Q3), width=.5) +
geom_line(size=.5) +
geom_point(size=1) +
facet_grid(.~f_m)+
theme(legend.position="top")+
xlab("Age Groups for proportions of pairings") + ylab("Proportion")
# OR
# plots.prop_pairings_100_target <- ggplot(d_f, aes(x=x, y=med, colour=f_m)) +
# geom_errorbar(aes(ymin=lower.Q1, ymax=upper.Q3), width=.5) +
# geom_line(size=.5) +
# geom_point(size=1) +
# # facet_grid(.~f_m)+
# theme(legend.position="top")+
# xlab("Age Groups for proportions of pairings") + ylab("Proportion")
print(plots.prop_pairings_100_target)## geom_path: Each group consists of only one observation. Do you need to
## adjust the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to
## adjust the group aesthetic?
ggsave(filename = "Plot_a_8_True_Proportion_of_Pairings_at_100_Coverage.pdf",
plot = plots.prop_pairings_100_target,
path = "/home/david/age_mixing_patterns_phylogenetic/results/MAR_a",
width = 26, height = 15, units = "cm")## geom_path: Each group consists of only one observation. Do you need to
## adjust the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to
## adjust the group aesthetic?4.2 Proportions in different sequence coverage scenarios: for pairings inferred from transmission clusters
Proportions of men/women inferred from pairings in transmission clusters.
# Extracting data
# Proportions of pairing of men/women across different age groups
# (i) transmission network built from transmission clusters
# .cl.prop.men
# .cl.prop.women
# (ii) true proportions in true transmission network of these individuals in transmission clusters
# .cl.true.prop.men
# .cl.true.prop.women
# MAR
d.MAR <- dr %>%
select(contains("MAR."))
d.MAR.cov.35 <- d.MAR %>%
select(contains("cov.MAR.a.35."))
d.MAR.cov.40 <- d.MAR %>%
select(contains("cov.MAR.a.40."))
d.MAR.cov.45 <- d.MAR %>%
select(contains("cov.MAR.a.45."))
d.MAR.cov.50 <- d.MAR %>%
select(contains("cov.MAR.a.50."))
d.MAR.cov.55 <- d.MAR %>%
select(contains("cov.MAR.a.55."))
d.MAR.cov.60 <- d.MAR %>%
select(contains("cov.MAR.a.60."))
d.MAR.cov.65 <- d.MAR %>%
select(contains("cov.MAR.a.65."))
d.MAR.cov.70 <- d.MAR %>%
select(contains("cov.MAR.a.70."))
d.MAR.cov.75 <- d.MAR %>%
select(contains("cov.MAR.a.75."))
d.MAR.cov.80 <- d.MAR %>%
select(contains("cov.MAR.a.80."))
d.MAR.cov.85 <- d.MAR %>%
select(contains("cov.MAR.a.85."))
d.MAR.cov.90 <- d.MAR %>%
select(contains("cov.MAR.a.90."))
d.MAR.cov.95 <- d.MAR %>%
select(contains("cov.MAR.a.95."))
d.MAR.cov.100 <- dr %>%
select(contains("cov.MCAR.100"))
# cov 35
d.MAR.cov.35.cl.prop.men <- d.MAR.cov.35 %>%
select(contains(".cl.prop.men")) # proportion of pairings inferred from transmission clusters
d.MAR.cov.35.cl.prop.women <- d.MAR.cov.35 %>%
select(contains(".cl.prop.women"))
d.MAR.cov.35.cl.true.prop.men <- d.MAR.cov.35 %>%
select(contains(".cl.true.prop.men")) # true proportion of pairings in transmission clusters
d.MAR.cov.35.cl.true.prop.women <- d.MAR.cov.35 %>%
select(contains(".cl.true.prop.women"))
# cov 40
d.MAR.cov.40.cl.prop.men <- d.MAR.cov.40 %>%
select(contains(".cl.prop.men")) # proportion of pairings inferred from transmission clusters
d.MAR.cov.40.cl.prop.women <- d.MAR.cov.40 %>%
select(contains(".cl.prop.women"))
d.MAR.cov.40.cl.true.prop.men <- d.MAR.cov.40 %>%
select(contains(".cl.true.prop.men")) # true proportion of pairings in transmission clusters
d.MAR.cov.40.cl.true.prop.women <- d.MAR.cov.40 %>%
select(contains(".cl.true.prop.women"))
# cov 45
d.MAR.cov.45.cl.prop.men <- d.MAR.cov.45 %>%
select(contains(".cl.prop.men")) # proportion of pairings inferred from transmission clusters
d.MAR.cov.45.cl.prop.women <- d.MAR.cov.45 %>%
select(contains(".cl.prop.women"))
d.MAR.cov.45.cl.true.prop.men <- d.MAR.cov.45 %>%
select(contains(".cl.true.prop.men")) # true proportion of pairings in transmission clusters
d.MAR.cov.45.cl.true.prop.women <- d.MAR.cov.45 %>%
select(contains(".cl.true.prop.women"))
# cov 50
d.MAR.cov.50.cl.prop.men <- d.MAR.cov.50 %>%
select(contains(".cl.prop.men")) # proportion of pairings inferred from transmission clusters
d.MAR.cov.50.cl.prop.women <- d.MAR.cov.50 %>%
select(contains(".cl.prop.women"))
d.MAR.cov.50.cl.true.prop.men <- d.MAR.cov.50 %>%
select(contains(".cl.true.prop.men")) # true proportion of pairings in transmission clusters
d.MAR.cov.50.cl.true.prop.women <- d.MAR.cov.50 %>%
select(contains(".cl.true.prop.women"))
# cov 55
d.MAR.cov.55.cl.prop.men <- d.MAR.cov.55 %>%
select(contains(".cl.prop.men")) # proportion of pairings inferred from transmission clusters
d.MAR.cov.55.cl.prop.women <- d.MAR.cov.55 %>%
select(contains(".cl.prop.women"))
d.MAR.cov.55.cl.true.prop.men <- d.MAR.cov.55 %>%
select(contains(".cl.true.prop.men")) # true proportion of pairings in transmission clusters
d.MAR.cov.55.cl.true.prop.women <- d.MAR.cov.55 %>%
select(contains(".cl.true.prop.women"))
# cov 60
d.MAR.cov.60.cl.prop.men <- d.MAR.cov.60 %>%
select(contains(".cl.prop.men")) # proportion of pairings inferred from transmission clusters
d.MAR.cov.60.cl.prop.women <- d.MAR.cov.60 %>%
select(contains(".cl.prop.women"))
d.MAR.cov.60.cl.true.prop.men <- d.MAR.cov.60 %>%
select(contains(".cl.true.prop.men")) # true proportion of pairings in transmission clusters
d.MAR.cov.60.cl.true.prop.women <- d.MAR.cov.60 %>%
select(contains(".cl.true.prop.women"))
# 65
d.MAR.cov.65.cl.prop.men <- d.MAR.cov.65 %>%
select(contains(".cl.prop.men")) # proportion of pairings inferred from transmission clusters
d.MAR.cov.65.cl.prop.women <- d.MAR.cov.65 %>%
select(contains(".cl.prop.women"))
d.MAR.cov.65.cl.true.prop.men <- d.MAR.cov.65 %>%
select(contains(".cl.true.prop.men")) # true proportion of pairings in transmission clusters
d.MAR.cov.65.cl.true.prop.women <- d.MAR.cov.65 %>%
select(contains(".cl.true.prop.women"))
# 70
d.MAR.cov.70.cl.prop.men <- d.MAR.cov.70 %>%
select(contains(".cl.prop.men")) # proportion of pairings inferred from transmission clusters
d.MAR.cov.70.cl.prop.women <- d.MAR.cov.70 %>%
select(contains(".cl.prop.women"))
d.MAR.cov.70.cl.true.prop.men <- d.MAR.cov.70 %>%
select(contains(".cl.true.prop.men")) # true proportion of pairings in transmission clusters
d.MAR.cov.70.cl.true.prop.women <- d.MAR.cov.70 %>%
select(contains(".cl.true.prop.women"))
# 75
d.MAR.cov.75.cl.prop.men <- d.MAR.cov.75 %>%
select(contains(".cl.prop.men")) # proportion of pairings inferred from transmission clusters
d.MAR.cov.75.cl.prop.women <- d.MAR.cov.75 %>%
select(contains(".cl.prop.women"))
d.MAR.cov.75.cl.true.prop.men <- d.MAR.cov.75 %>%
select(contains(".cl.true.prop.men")) # true proportion of pairings in transmission clusters
d.MAR.cov.75.cl.true.prop.women <- d.MAR.cov.75 %>%
select(contains(".cl.true.prop.women"))
# cov 80
d.MAR.cov.80.cl.prop.men <- d.MAR.cov.80 %>%
select(contains(".cl.prop.men")) # proportion of pairings inferred from transmission clusters
d.MAR.cov.80.cl.prop.women <- d.MAR.cov.80 %>%
select(contains(".cl.prop.women"))
d.MAR.cov.80.cl.true.prop.men <- d.MAR.cov.80 %>%
select(contains(".cl.true.prop.men")) # true proportion of pairings in transmission clusters
d.MAR.cov.80.cl.true.prop.women <- d.MAR.cov.80 %>%
select(contains(".cl.true.prop.women"))
# cov 85
d.MAR.cov.85.cl.prop.men <- d.MAR.cov.85 %>%
select(contains(".cl.prop.men")) # proportion of pairings inferred from transmission clusters
d.MAR.cov.85.cl.prop.women <- d.MAR.cov.85 %>%
select(contains(".cl.prop.women"))
d.MAR.cov.85.cl.true.prop.men <- d.MAR.cov.85 %>%
select(contains(".cl.true.prop.men")) # true proportion of pairings in transmission clusters
d.MAR.cov.85.cl.true.prop.women <- d.MAR.cov.85 %>%
select(contains(".cl.true.prop.women"))
# cov 90
d.MAR.cov.90.cl.prop.men <- d.MAR.cov.90 %>%
select(contains(".cl.prop.men")) # proportion of pairings inferred from transmission clusters
d.MAR.cov.90.cl.prop.women <- d.MAR.cov.90 %>%
select(contains(".cl.prop.women"))
d.MAR.cov.90.cl.true.prop.men <- d.MAR.cov.90 %>%
select(contains(".cl.true.prop.men")) # true proportion of pairings in transmission clusters
d.MAR.cov.90.cl.true.prop.women <- d.MAR.cov.90 %>%
select(contains(".cl.true.prop.women"))
# cov 95
d.MAR.cov.95.cl.prop.men <- d.MAR.cov.95 %>%
select(contains(".cl.prop.men")) # proportion of pairings inferred from transmission clusters
d.MAR.cov.95.cl.prop.women <- d.MAR.cov.95 %>%
select(contains(".cl.prop.women"))
d.MAR.cov.95.cl.true.prop.men <- d.MAR.cov.95 %>%
select(contains(".cl.true.prop.men")) # true proportion of pairings in transmission clusters
d.MAR.cov.95.cl.true.prop.women <- d.MAR.cov.95 %>%
select(contains(".cl.true.prop.women"))
# proportions computation
# Cov 35
# Vectors
vector.MAR.cov.35.cl.prop.men15.25.F.15.25 <- d.MAR.cov.35.cl.prop.men[,1]
vector.MAR.cov.35.cl.prop.women15.25.M.15.25 <- d.MAR.cov.35.cl.prop.women[,1]
vector.MAR.cov.35.cl.prop.men25.40.F.15.25 <- d.MAR.cov.35.cl.prop.men[,2]
vector.MAR.cov.35.cl.prop.women25.40.M.15.25 <- d.MAR.cov.35.cl.prop.women[,2]
vector.MAR.cov.35.cl.prop.men40.50.F.15.25 <- d.MAR.cov.35.cl.prop.men[,3]
vector.MAR.cov.35.cl.prop.women40.50.M.15.25 <- d.MAR.cov.35.cl.prop.women[,3]
vector.MAR.cov.35.cl.prop.men15.25.F.25.40 <- d.MAR.cov.35.cl.prop.men[,4]
vector.MAR.cov.35.cl.prop.women15.25.M.25.40 <- d.MAR.cov.35.cl.prop.women[,4]
vector.MAR.cov.35.cl.prop.men25.40.F.25.40 <- d.MAR.cov.35.cl.prop.men[,5]
vector.MAR.cov.35.cl.prop.women25.40.M.25.40 <- d.MAR.cov.35.cl.prop.women[,5]
vector.MAR.cov.35.cl.prop.men40.50.F.25.40 <- d.MAR.cov.35.cl.prop.men[,6]
vector.MAR.cov.35.cl.prop.women40.50.M.25.40 <- d.MAR.cov.35.cl.prop.women[,6]
vector.MAR.cov.35.cl.prop.men15.25.F.40.50 <- d.MAR.cov.35.cl.prop.men[,7]
vector.MAR.cov.35.cl.prop.women15.25.M.40.50 <- d.MAR.cov.35.cl.prop.women[,7]
vector.MAR.cov.35.cl.prop.men25.40.F.40.50 <- d.MAR.cov.35.cl.prop.men[,8]
vector.MAR.cov.35.cl.prop.women25.40.M.40.50 <- d.MAR.cov.35.cl.prop.women[,8]
vector.MAR.cov.35.cl.prop.men40.50.F.40.50 <- d.MAR.cov.35.cl.prop.men[,9]
vector.MAR.cov.35.cl.prop.women40.50.M.40.50 <- d.MAR.cov.35.cl.prop.women[,9]
# Summarised
d.MAR.cov.35.cl.prop.men15.25.F.15.25 <- quant.med(d.MAR.cov.35.cl.prop.men[,1])
d.MAR.cov.35.cl.prop.women15.25.M.15.25 <- quant.med(d.MAR.cov.35.cl.prop.women[,1])
d.MAR.cov.35.cl.prop.men25.40.F.15.25 <- quant.med(d.MAR.cov.35.cl.prop.men[,2])
d.MAR.cov.35.cl.prop.women25.40.M.15.25 <- quant.med(d.MAR.cov.35.cl.prop.women[,2])
d.MAR.cov.35.cl.prop.men40.50.F.15.25 <- quant.med(d.MAR.cov.35.cl.prop.men[,3])
d.MAR.cov.35.cl.prop.women40.50.M.15.25 <- quant.med(d.MAR.cov.35.cl.prop.women[,3])
d.MAR.cov.35.cl.prop.men15.25.F.25.40 <- quant.med(d.MAR.cov.35.cl.prop.men[,4])
d.MAR.cov.35.cl.prop.women15.25.M.25.40 <- quant.med(d.MAR.cov.35.cl.prop.women[,4])
d.MAR.cov.35.cl.prop.men25.40.F.25.40 <- quant.med(d.MAR.cov.35.cl.prop.men[,5])
d.MAR.cov.35.cl.prop.women25.40.M.25.40 <- quant.med(d.MAR.cov.35.cl.prop.women[,5])
d.MAR.cov.35.cl.prop.men40.50.F.25.40 <- quant.med(d.MAR.cov.35.cl.prop.men[,6])
d.MAR.cov.35.cl.prop.women40.50.M.25.40 <- quant.med(d.MAR.cov.35.cl.prop.women[,6])
d.MAR.cov.35.cl.prop.men15.25.F.40.50 <- quant.med(d.MAR.cov.35.cl.prop.men[,7])
d.MAR.cov.35.cl.prop.women15.25.M.40.50 <- quant.med(d.MAR.cov.35.cl.prop.women[,7])
d.MAR.cov.35.cl.prop.men25.40.F.40.50 <- quant.med(d.MAR.cov.35.cl.prop.men[,8])
d.MAR.cov.35.cl.prop.women25.40.M.40.50 <- quant.med(d.MAR.cov.35.cl.prop.women[,8])
d.MAR.cov.35.cl.prop.men40.50.F.40.50 <- quant.med(d.MAR.cov.35.cl.prop.men[,9])
d.MAR.cov.35.cl.prop.women40.50.M.40.50 <- quant.med(d.MAR.cov.35.cl.prop.women[,9])
# Cov 40
# Vector
vector.MAR.cov.40.cl.prop.men15.25.F.15.25 <- d.MAR.cov.40.cl.prop.men[,1]
vector.MAR.cov.40.cl.prop.women15.25.M.15.25 <- d.MAR.cov.40.cl.prop.women[,1]
vector.MAR.cov.40.cl.prop.men25.40.F.15.25 <- d.MAR.cov.40.cl.prop.men[,2]
vector.MAR.cov.40.cl.prop.women25.40.M.15.25 <- d.MAR.cov.40.cl.prop.women[,2]
vector.MAR.cov.40.cl.prop.men40.50.F.15.25 <- d.MAR.cov.40.cl.prop.men[,3]
vector.MAR.cov.40.cl.prop.women40.50.M.15.25 <- d.MAR.cov.40.cl.prop.women[,3]
vector.MAR.cov.40.cl.prop.men15.25.F.25.40 <- d.MAR.cov.40.cl.prop.men[,4]
vector.MAR.cov.40.cl.prop.women15.25.M.25.40 <- d.MAR.cov.40.cl.prop.women[,4]
vector.MAR.cov.40.cl.prop.men25.40.F.25.40 <- d.MAR.cov.40.cl.prop.men[,5]
vector.MAR.cov.40.cl.prop.women25.40.M.25.40 <- d.MAR.cov.40.cl.prop.women[,5]
vector.MAR.cov.40.cl.prop.men40.50.F.25.40 <- d.MAR.cov.40.cl.prop.men[,6]
vector.MAR.cov.40.cl.prop.women40.50.M.25.40 <- d.MAR.cov.40.cl.prop.women[,6]
vector.MAR.cov.40.cl.prop.men15.25.F.40.50 <- d.MAR.cov.40.cl.prop.men[,7]
vector.MAR.cov.40.cl.prop.women15.25.M.40.50 <- d.MAR.cov.40.cl.prop.women[,7]
vector.MAR.cov.40.cl.prop.men25.40.F.40.50 <- d.MAR.cov.40.cl.prop.men[,8]
vector.MAR.cov.40.cl.prop.women25.40.M.40.50 <- d.MAR.cov.40.cl.prop.women[,8]
vector.MAR.cov.40.cl.prop.men40.50.F.40.50 <- d.MAR.cov.40.cl.prop.men[,9]
vector.MAR.cov.40.cl.prop.women40.50.M.40.50 <- d.MAR.cov.40.cl.prop.women[,9]
# Summarised
d.MAR.cov.40.cl.prop.men15.25.F.15.25 <- quant.med(d.MAR.cov.40.cl.prop.men[,1])
d.MAR.cov.40.cl.prop.women15.25.M.15.25 <- quant.med(d.MAR.cov.40.cl.prop.women[,1])
d.MAR.cov.40.cl.prop.men25.40.F.15.25 <- quant.med(d.MAR.cov.40.cl.prop.men[,2])
d.MAR.cov.40.cl.prop.women25.40.M.15.25 <- quant.med(d.MAR.cov.40.cl.prop.women[,2])
d.MAR.cov.40.cl.prop.men40.50.F.15.25 <- quant.med(d.MAR.cov.40.cl.prop.men[,3])
d.MAR.cov.40.cl.prop.women40.50.M.15.25 <- quant.med(d.MAR.cov.40.cl.prop.women[,3])
d.MAR.cov.40.cl.prop.men15.25.F.25.40 <- quant.med(d.MAR.cov.40.cl.prop.men[,4])
d.MAR.cov.40.cl.prop.women15.25.M.25.40 <- quant.med(d.MAR.cov.40.cl.prop.women[,4])
d.MAR.cov.40.cl.prop.men25.40.F.25.40 <- quant.med(d.MAR.cov.40.cl.prop.men[,5])
d.MAR.cov.40.cl.prop.women25.40.M.25.40 <- quant.med(d.MAR.cov.40.cl.prop.women[,5])
d.MAR.cov.40.cl.prop.men40.50.F.25.40 <- quant.med(d.MAR.cov.40.cl.prop.men[,6])
d.MAR.cov.40.cl.prop.women40.50.M.25.40 <- quant.med(d.MAR.cov.40.cl.prop.women[,6])
d.MAR.cov.40.cl.prop.men15.25.F.40.50 <- quant.med(d.MAR.cov.40.cl.prop.men[,7])
d.MAR.cov.40.cl.prop.women15.25.M.40.50 <- quant.med(d.MAR.cov.40.cl.prop.women[,7])
d.MAR.cov.40.cl.prop.men25.40.F.40.50 <- quant.med(d.MAR.cov.40.cl.prop.men[,8])
d.MAR.cov.40.cl.prop.women25.40.M.40.50 <- quant.med(d.MAR.cov.40.cl.prop.women[,8])
d.MAR.cov.40.cl.prop.men40.50.F.40.50 <- quant.med(d.MAR.cov.40.cl.prop.men[,9])
d.MAR.cov.40.cl.prop.women40.50.M.40.50 <- quant.med(d.MAR.cov.40.cl.prop.women[,9])
# Cov 45
# Vector
vector.MAR.cov.45.cl.prop.men15.25.F.15.25 <- d.MAR.cov.45.cl.prop.men[,1]
vector.MAR.cov.45.cl.prop.women15.25.M.15.25 <- d.MAR.cov.45.cl.prop.women[,1]
vector.MAR.cov.45.cl.prop.men25.40.F.15.25 <- d.MAR.cov.45.cl.prop.men[,2]
vector.MAR.cov.45.cl.prop.women25.40.M.15.25 <- d.MAR.cov.45.cl.prop.women[,2]
vector.MAR.cov.45.cl.prop.men40.50.F.15.25 <- d.MAR.cov.45.cl.prop.men[,3]
vector.MAR.cov.45.cl.prop.women40.50.M.15.25 <- d.MAR.cov.45.cl.prop.women[,3]
vector.MAR.cov.45.cl.prop.men15.25.F.25.40 <- d.MAR.cov.45.cl.prop.men[,4]
vector.MAR.cov.45.cl.prop.women15.25.M.25.40 <- d.MAR.cov.45.cl.prop.women[,4]
vector.MAR.cov.45.cl.prop.men25.40.F.25.40 <- d.MAR.cov.45.cl.prop.men[,5]
vector.MAR.cov.45.cl.prop.women25.40.M.25.40 <- d.MAR.cov.45.cl.prop.women[,5]
vector.MAR.cov.45.cl.prop.men40.50.F.25.40 <- d.MAR.cov.45.cl.prop.men[,6]
vector.MAR.cov.45.cl.prop.women40.50.M.25.40 <- d.MAR.cov.45.cl.prop.women[,6]
vector.MAR.cov.45.cl.prop.men15.25.F.40.50 <- d.MAR.cov.45.cl.prop.men[,7]
vector.MAR.cov.45.cl.prop.women15.25.M.40.50 <- d.MAR.cov.45.cl.prop.women[,7]
vector.MAR.cov.45.cl.prop.men25.40.F.40.50 <- d.MAR.cov.45.cl.prop.men[,8]
vector.MAR.cov.45.cl.prop.women25.40.M.40.50 <- d.MAR.cov.45.cl.prop.women[,8]
vector.MAR.cov.45.cl.prop.men40.50.F.40.50 <- d.MAR.cov.45.cl.prop.men[,9]
vector.MAR.cov.45.cl.prop.women40.50.M.40.50 <- d.MAR.cov.45.cl.prop.women[,9]
# Summarised
d.MAR.cov.45.cl.prop.men15.25.F.15.25 <- quant.med(d.MAR.cov.45.cl.prop.men[,1])
d.MAR.cov.45.cl.prop.women15.25.M.15.25 <- quant.med(d.MAR.cov.45.cl.prop.women[,1])
d.MAR.cov.45.cl.prop.men25.40.F.15.25 <- quant.med(d.MAR.cov.45.cl.prop.men[,2])
d.MAR.cov.45.cl.prop.women25.40.M.15.25 <- quant.med(d.MAR.cov.45.cl.prop.women[,2])
d.MAR.cov.45.cl.prop.men40.50.F.15.25 <- quant.med(d.MAR.cov.45.cl.prop.men[,3])
d.MAR.cov.45.cl.prop.women40.50.M.15.25 <- quant.med(d.MAR.cov.45.cl.prop.women[,3])
d.MAR.cov.45.cl.prop.men15.25.F.25.40 <- quant.med(d.MAR.cov.45.cl.prop.men[,4])
d.MAR.cov.45.cl.prop.women15.25.M.25.40 <- quant.med(d.MAR.cov.45.cl.prop.women[,4])
d.MAR.cov.45.cl.prop.men25.40.F.25.40 <- quant.med(d.MAR.cov.45.cl.prop.men[,5])
d.MAR.cov.45.cl.prop.women25.40.M.25.40 <- quant.med(d.MAR.cov.45.cl.prop.women[,5])
d.MAR.cov.45.cl.prop.men40.50.F.25.40 <- quant.med(d.MAR.cov.45.cl.prop.men[,6])
d.MAR.cov.45.cl.prop.women40.50.M.25.40 <- quant.med(d.MAR.cov.45.cl.prop.women[,6])
d.MAR.cov.45.cl.prop.men15.25.F.40.50 <- quant.med(d.MAR.cov.45.cl.prop.men[,7])
d.MAR.cov.45.cl.prop.women15.25.M.40.50 <- quant.med(d.MAR.cov.45.cl.prop.women[,7])
d.MAR.cov.45.cl.prop.men25.40.F.40.50 <- quant.med(d.MAR.cov.45.cl.prop.men[,8])
d.MAR.cov.45.cl.prop.women25.40.M.40.50 <- quant.med(d.MAR.cov.45.cl.prop.women[,8])
d.MAR.cov.45.cl.prop.men40.50.F.40.50 <- quant.med(d.MAR.cov.45.cl.prop.men[,9])
d.MAR.cov.45.cl.prop.women40.50.M.40.50 <- quant.med(d.MAR.cov.45.cl.prop.women[,9])
# Cov 50
# Vector
vector.MAR.cov.50.cl.prop.men15.25.F.15.25 <- d.MAR.cov.50.cl.prop.men[,1]
vector.MAR.cov.50.cl.prop.women15.25.M.15.25 <- d.MAR.cov.50.cl.prop.women[,1]
vector.MAR.cov.50.cl.prop.men25.40.F.15.25 <- d.MAR.cov.50.cl.prop.men[,2]
vector.MAR.cov.50.cl.prop.women25.40.M.15.25 <- d.MAR.cov.50.cl.prop.women[,2]
vector.MAR.cov.50.cl.prop.men40.50.F.15.25 <- d.MAR.cov.50.cl.prop.men[,3]
vector.MAR.cov.50.cl.prop.women40.50.M.15.25 <- d.MAR.cov.50.cl.prop.women[,3]
vector.MAR.cov.50.cl.prop.men15.25.F.25.40 <- d.MAR.cov.50.cl.prop.men[,4]
vector.MAR.cov.50.cl.prop.women15.25.M.25.40 <- d.MAR.cov.50.cl.prop.women[,4]
vector.MAR.cov.50.cl.prop.men25.40.F.25.40 <- d.MAR.cov.50.cl.prop.men[,5]
vector.MAR.cov.50.cl.prop.women25.40.M.25.40 <- d.MAR.cov.50.cl.prop.women[,5]
vector.MAR.cov.50.cl.prop.men40.50.F.25.40 <- d.MAR.cov.50.cl.prop.men[,6]
vector.MAR.cov.50.cl.prop.women40.50.M.25.40 <- d.MAR.cov.50.cl.prop.women[,6]
vector.MAR.cov.50.cl.prop.men15.25.F.40.50 <- d.MAR.cov.50.cl.prop.men[,7]
vector.MAR.cov.50.cl.prop.women15.25.M.40.50 <- d.MAR.cov.50.cl.prop.women[,7]
vector.MAR.cov.50.cl.prop.men25.40.F.40.50 <- d.MAR.cov.50.cl.prop.men[,8]
vector.MAR.cov.50.cl.prop.women25.40.M.40.50 <- d.MAR.cov.50.cl.prop.women[,8]
vector.MAR.cov.50.cl.prop.men40.50.F.40.50 <- d.MAR.cov.50.cl.prop.men[,9]
vector.MAR.cov.50.cl.prop.women40.50.M.40.50 <- d.MAR.cov.50.cl.prop.women[,9]
# Summarised
d.MAR.cov.50.cl.prop.men15.25.F.15.25 <- quant.med(d.MAR.cov.50.cl.prop.men[,1])
d.MAR.cov.50.cl.prop.women15.25.M.15.25 <- quant.med(d.MAR.cov.50.cl.prop.women[,1])
d.MAR.cov.50.cl.prop.men25.40.F.15.25 <- quant.med(d.MAR.cov.50.cl.prop.men[,2])
d.MAR.cov.50.cl.prop.women25.40.M.15.25 <- quant.med(d.MAR.cov.50.cl.prop.women[,2])
d.MAR.cov.50.cl.prop.men40.50.F.15.25 <- quant.med(d.MAR.cov.50.cl.prop.men[,3])
d.MAR.cov.50.cl.prop.women40.50.M.15.25 <- quant.med(d.MAR.cov.50.cl.prop.women[,3])
d.MAR.cov.50.cl.prop.men15.25.F.25.40 <- quant.med(d.MAR.cov.50.cl.prop.men[,4])
d.MAR.cov.50.cl.prop.women15.25.M.25.40 <- quant.med(d.MAR.cov.50.cl.prop.women[,4])
d.MAR.cov.50.cl.prop.men25.40.F.25.40 <- quant.med(d.MAR.cov.50.cl.prop.men[,5])
d.MAR.cov.50.cl.prop.women25.40.M.25.40 <- quant.med(d.MAR.cov.50.cl.prop.women[,5])
d.MAR.cov.50.cl.prop.men40.50.F.25.40 <- quant.med(d.MAR.cov.50.cl.prop.men[,6])
d.MAR.cov.50.cl.prop.women40.50.M.25.40 <- quant.med(d.MAR.cov.50.cl.prop.women[,6])
d.MAR.cov.50.cl.prop.men15.25.F.40.50 <- quant.med(d.MAR.cov.50.cl.prop.men[,7])
d.MAR.cov.50.cl.prop.women15.25.M.40.50 <- quant.med(d.MAR.cov.50.cl.prop.women[,7])
d.MAR.cov.50.cl.prop.men25.40.F.40.50 <- quant.med(d.MAR.cov.50.cl.prop.men[,8])
d.MAR.cov.50.cl.prop.women25.40.M.40.50 <- quant.med(d.MAR.cov.50.cl.prop.women[,8])
d.MAR.cov.50.cl.prop.men40.50.F.40.50 <- quant.med(d.MAR.cov.50.cl.prop.men[,9])
d.MAR.cov.50.cl.prop.women40.50.M.40.50 <- quant.med(d.MAR.cov.50.cl.prop.women[,9])
# Cov 55
# Vector
vector.MAR.cov.55.cl.prop.men15.25.F.15.25 <- d.MAR.cov.55.cl.prop.men[,1]
vector.MAR.cov.55.cl.prop.women15.25.M.15.25 <- d.MAR.cov.55.cl.prop.women[,1]
vector.MAR.cov.55.cl.prop.men25.40.F.15.25 <- d.MAR.cov.55.cl.prop.men[,2]
vector.MAR.cov.55.cl.prop.women25.40.M.15.25 <- d.MAR.cov.55.cl.prop.women[,2]
vector.MAR.cov.55.cl.prop.men40.50.F.15.25 <- d.MAR.cov.55.cl.prop.men[,3]
vector.MAR.cov.55.cl.prop.women40.50.M.15.25 <- d.MAR.cov.55.cl.prop.women[,3]
vector.MAR.cov.55.cl.prop.men15.25.F.25.40 <- d.MAR.cov.55.cl.prop.men[,4]
vector.MAR.cov.55.cl.prop.women15.25.M.25.40 <- d.MAR.cov.55.cl.prop.women[,4]
vector.MAR.cov.55.cl.prop.men25.40.F.25.40 <- d.MAR.cov.55.cl.prop.men[,5]
vector.MAR.cov.55.cl.prop.women25.40.M.25.40 <- d.MAR.cov.55.cl.prop.women[,5]
vector.MAR.cov.55.cl.prop.men40.50.F.25.40 <- d.MAR.cov.55.cl.prop.men[,6]
vector.MAR.cov.55.cl.prop.women40.50.M.25.40 <- d.MAR.cov.55.cl.prop.women[,6]
vector.MAR.cov.55.cl.prop.men15.25.F.40.50 <- d.MAR.cov.55.cl.prop.men[,7]
vector.MAR.cov.55.cl.prop.women15.25.M.40.50 <- d.MAR.cov.55.cl.prop.women[,7]
vector.MAR.cov.55.cl.prop.men25.40.F.40.50 <- d.MAR.cov.55.cl.prop.men[,8]
vector.MAR.cov.55.cl.prop.women25.40.M.40.50 <- d.MAR.cov.55.cl.prop.women[,8]
vector.MAR.cov.55.cl.prop.men40.50.F.40.50 <- d.MAR.cov.55.cl.prop.men[,9]
vector.MAR.cov.55.cl.prop.women40.50.M.40.50 <- d.MAR.cov.55.cl.prop.women[,9]
# Summarised
d.MAR.cov.55.cl.prop.men15.25.F.15.25 <- quant.med(d.MAR.cov.55.cl.prop.men[,1])
d.MAR.cov.55.cl.prop.women15.25.M.15.25 <- quant.med(d.MAR.cov.55.cl.prop.women[,1])
d.MAR.cov.55.cl.prop.men25.40.F.15.25 <- quant.med(d.MAR.cov.55.cl.prop.men[,2])
d.MAR.cov.55.cl.prop.women25.40.M.15.25 <- quant.med(d.MAR.cov.55.cl.prop.women[,2])
d.MAR.cov.55.cl.prop.men40.50.F.15.25 <- quant.med(d.MAR.cov.55.cl.prop.men[,3])
d.MAR.cov.55.cl.prop.women40.50.M.15.25 <- quant.med(d.MAR.cov.55.cl.prop.women[,3])
d.MAR.cov.55.cl.prop.men15.25.F.25.40 <- quant.med(d.MAR.cov.55.cl.prop.men[,4])
d.MAR.cov.55.cl.prop.women15.25.M.25.40 <- quant.med(d.MAR.cov.55.cl.prop.women[,4])
d.MAR.cov.55.cl.prop.men25.40.F.25.40 <- quant.med(d.MAR.cov.55.cl.prop.men[,5])
d.MAR.cov.55.cl.prop.women25.40.M.25.40 <- quant.med(d.MAR.cov.55.cl.prop.women[,5])
d.MAR.cov.55.cl.prop.men40.50.F.25.40 <- quant.med(d.MAR.cov.55.cl.prop.men[,6])
d.MAR.cov.55.cl.prop.women40.50.M.25.40 <- quant.med(d.MAR.cov.55.cl.prop.women[,6])
d.MAR.cov.55.cl.prop.men15.25.F.40.50 <- quant.med(d.MAR.cov.55.cl.prop.men[,7])
d.MAR.cov.55.cl.prop.women15.25.M.40.50 <- quant.med(d.MAR.cov.55.cl.prop.women[,7])
d.MAR.cov.55.cl.prop.men25.40.F.40.50 <- quant.med(d.MAR.cov.55.cl.prop.men[,8])
d.MAR.cov.55.cl.prop.women25.40.M.40.50 <- quant.med(d.MAR.cov.55.cl.prop.women[,8])
d.MAR.cov.55.cl.prop.men40.50.F.40.50 <- quant.med(d.MAR.cov.55.cl.prop.men[,9])
d.MAR.cov.55.cl.prop.women40.50.M.40.50 <- quant.med(d.MAR.cov.55.cl.prop.women[,9])
# Cov 60
# Vector
vector.MAR.cov.60.cl.prop.men15.25.F.15.25 <- d.MAR.cov.60.cl.prop.men[,1]
vector.MAR.cov.60.cl.prop.women15.25.M.15.25 <- d.MAR.cov.60.cl.prop.women[,1]
vector.MAR.cov.60.cl.prop.men25.40.F.15.25 <- d.MAR.cov.60.cl.prop.men[,2]
vector.MAR.cov.60.cl.prop.women25.40.M.15.25 <- d.MAR.cov.60.cl.prop.women[,2]
vector.MAR.cov.60.cl.prop.men40.50.F.15.25 <- d.MAR.cov.60.cl.prop.men[,3]
vector.MAR.cov.60.cl.prop.women40.50.M.15.25 <- d.MAR.cov.60.cl.prop.women[,3]
vector.MAR.cov.60.cl.prop.men15.25.F.25.40 <- d.MAR.cov.60.cl.prop.men[,4]
vector.MAR.cov.60.cl.prop.women15.25.M.25.40 <- d.MAR.cov.60.cl.prop.women[,4]
vector.MAR.cov.60.cl.prop.men25.40.F.25.40 <- d.MAR.cov.60.cl.prop.men[,5]
vector.MAR.cov.60.cl.prop.women25.40.M.25.40 <- d.MAR.cov.60.cl.prop.women[,5]
vector.MAR.cov.60.cl.prop.men40.50.F.25.40 <- d.MAR.cov.60.cl.prop.men[,6]
vector.MAR.cov.60.cl.prop.women40.50.M.25.40 <- d.MAR.cov.60.cl.prop.women[,6]
vector.MAR.cov.60.cl.prop.men15.25.F.40.50 <- d.MAR.cov.60.cl.prop.men[,7]
vector.MAR.cov.60.cl.prop.women15.25.M.40.50 <- d.MAR.cov.60.cl.prop.women[,7]
vector.MAR.cov.60.cl.prop.men25.40.F.40.50 <- d.MAR.cov.60.cl.prop.men[,8]
vector.MAR.cov.60.cl.prop.women25.40.M.40.50 <- d.MAR.cov.60.cl.prop.women[,8]
vector.MAR.cov.60.cl.prop.men40.50.F.40.50 <- d.MAR.cov.60.cl.prop.men[,9]
vector.MAR.cov.60.cl.prop.women40.50.M.40.50 <- d.MAR.cov.60.cl.prop.women[,9]
# Summarised
d.MAR.cov.60.cl.prop.men15.25.F.15.25 <- quant.med(d.MAR.cov.60.cl.prop.men[,1])
d.MAR.cov.60.cl.prop.women15.25.M.15.25 <- quant.med(d.MAR.cov.60.cl.prop.women[,1])
d.MAR.cov.60.cl.prop.men25.40.F.15.25 <- quant.med(d.MAR.cov.60.cl.prop.men[,2])
d.MAR.cov.60.cl.prop.women25.40.M.15.25 <- quant.med(d.MAR.cov.60.cl.prop.women[,2])
d.MAR.cov.60.cl.prop.men40.50.F.15.25 <- quant.med(d.MAR.cov.60.cl.prop.men[,3])
d.MAR.cov.60.cl.prop.women40.50.M.15.25 <- quant.med(d.MAR.cov.60.cl.prop.women[,3])
d.MAR.cov.60.cl.prop.men15.25.F.25.40 <- quant.med(d.MAR.cov.60.cl.prop.men[,4])
d.MAR.cov.60.cl.prop.women15.25.M.25.40 <- quant.med(d.MAR.cov.60.cl.prop.women[,4])
d.MAR.cov.60.cl.prop.men25.40.F.25.40 <- quant.med(d.MAR.cov.60.cl.prop.men[,5])
d.MAR.cov.60.cl.prop.women25.40.M.25.40 <- quant.med(d.MAR.cov.60.cl.prop.women[,5])
d.MAR.cov.60.cl.prop.men40.50.F.25.40 <- quant.med(d.MAR.cov.60.cl.prop.men[,6])
d.MAR.cov.60.cl.prop.women40.50.M.25.40 <- quant.med(d.MAR.cov.60.cl.prop.women[,6])
d.MAR.cov.60.cl.prop.men15.25.F.40.50 <- quant.med(d.MAR.cov.60.cl.prop.men[,7])
d.MAR.cov.60.cl.prop.women15.25.M.40.50 <- quant.med(d.MAR.cov.60.cl.prop.women[,7])
d.MAR.cov.60.cl.prop.men25.40.F.40.50 <- quant.med(d.MAR.cov.60.cl.prop.men[,8])
d.MAR.cov.60.cl.prop.women25.40.M.40.50 <- quant.med(d.MAR.cov.60.cl.prop.women[,8])
d.MAR.cov.60.cl.prop.men40.50.F.40.50 <- quant.med(d.MAR.cov.60.cl.prop.men[,9])
d.MAR.cov.60.cl.prop.women40.50.M.40.50 <- quant.med(d.MAR.cov.60.cl.prop.women[,9])
# Cov 65
# Vector
vector.MAR.cov.65.cl.prop.men15.25.F.15.25 <- d.MAR.cov.65.cl.prop.men[,1]
vector.MAR.cov.65.cl.prop.women15.25.M.15.25 <- d.MAR.cov.65.cl.prop.women[,1]
vector.MAR.cov.65.cl.prop.men25.40.F.15.25 <- d.MAR.cov.65.cl.prop.men[,2]
vector.MAR.cov.65.cl.prop.women25.40.M.15.25 <- d.MAR.cov.65.cl.prop.women[,2]
vector.MAR.cov.65.cl.prop.men40.50.F.15.25 <- d.MAR.cov.65.cl.prop.men[,3]
vector.MAR.cov.65.cl.prop.women40.50.M.15.25 <- d.MAR.cov.65.cl.prop.women[,3]
vector.MAR.cov.65.cl.prop.men15.25.F.25.40 <- d.MAR.cov.65.cl.prop.men[,4]
vector.MAR.cov.65.cl.prop.women15.25.M.25.40 <- d.MAR.cov.65.cl.prop.women[,4]
vector.MAR.cov.65.cl.prop.men25.40.F.25.40 <- d.MAR.cov.65.cl.prop.men[,5]
vector.MAR.cov.65.cl.prop.women25.40.M.25.40 <- d.MAR.cov.65.cl.prop.women[,5]
vector.MAR.cov.65.cl.prop.men40.50.F.25.40 <- d.MAR.cov.65.cl.prop.men[,6]
vector.MAR.cov.65.cl.prop.women40.50.M.25.40 <- d.MAR.cov.65.cl.prop.women[,6]
vector.MAR.cov.65.cl.prop.men15.25.F.40.50 <- d.MAR.cov.65.cl.prop.men[,7]
vector.MAR.cov.65.cl.prop.women15.25.M.40.50 <- d.MAR.cov.65.cl.prop.women[,7]
vector.MAR.cov.65.cl.prop.men25.40.F.40.50 <- d.MAR.cov.65.cl.prop.men[,8]
vector.MAR.cov.65.cl.prop.women25.40.M.40.50 <- d.MAR.cov.65.cl.prop.women[,8]
vector.MAR.cov.65.cl.prop.men40.50.F.40.50 <- d.MAR.cov.65.cl.prop.men[,9]
vector.MAR.cov.65.cl.prop.women40.50.M.40.50 <- d.MAR.cov.65.cl.prop.women[,9]
# Summarised
d.MAR.cov.65.cl.prop.men15.25.F.15.25 <- quant.med(d.MAR.cov.65.cl.prop.men[,1])
d.MAR.cov.65.cl.prop.women15.25.M.15.25 <- quant.med(d.MAR.cov.65.cl.prop.women[,1])
d.MAR.cov.65.cl.prop.men25.40.F.15.25 <- quant.med(d.MAR.cov.65.cl.prop.men[,2])
d.MAR.cov.65.cl.prop.women25.40.M.15.25 <- quant.med(d.MAR.cov.65.cl.prop.women[,2])
d.MAR.cov.65.cl.prop.men40.50.F.15.25 <- quant.med(d.MAR.cov.65.cl.prop.men[,3])
d.MAR.cov.65.cl.prop.women40.50.M.15.25 <- quant.med(d.MAR.cov.65.cl.prop.women[,3])
d.MAR.cov.65.cl.prop.men15.25.F.25.40 <- quant.med(d.MAR.cov.65.cl.prop.men[,4])
d.MAR.cov.65.cl.prop.women15.25.M.25.40 <- quant.med(d.MAR.cov.65.cl.prop.women[,4])
d.MAR.cov.65.cl.prop.men25.40.F.25.40 <- quant.med(d.MAR.cov.65.cl.prop.men[,5])
d.MAR.cov.65.cl.prop.women25.40.M.25.40 <- quant.med(d.MAR.cov.65.cl.prop.women[,5])
d.MAR.cov.65.cl.prop.men40.50.F.25.40 <- quant.med(d.MAR.cov.65.cl.prop.men[,6])
d.MAR.cov.65.cl.prop.women40.50.M.25.40 <- quant.med(d.MAR.cov.65.cl.prop.women[,6])
d.MAR.cov.65.cl.prop.men15.25.F.40.50 <- quant.med(d.MAR.cov.65.cl.prop.men[,7])
d.MAR.cov.65.cl.prop.women15.25.M.40.50 <- quant.med(d.MAR.cov.65.cl.prop.women[,7])
d.MAR.cov.65.cl.prop.men25.40.F.40.50 <- quant.med(d.MAR.cov.65.cl.prop.men[,8])
d.MAR.cov.65.cl.prop.women25.40.M.40.50 <- quant.med(d.MAR.cov.65.cl.prop.women[,8])
d.MAR.cov.65.cl.prop.men40.50.F.40.50 <- quant.med(d.MAR.cov.65.cl.prop.men[,9])
d.MAR.cov.65.cl.prop.women40.50.M.40.50 <- quant.med(d.MAR.cov.65.cl.prop.women[,9])
# Cov 70
# Vector
vector.MAR.cov.70.cl.prop.men15.25.F.15.25 <- d.MAR.cov.70.cl.prop.men[,1]
vector.MAR.cov.70.cl.prop.women15.25.M.15.25 <- d.MAR.cov.70.cl.prop.women[,1]
vector.MAR.cov.70.cl.prop.men25.40.F.15.25 <- d.MAR.cov.70.cl.prop.men[,2]
vector.MAR.cov.70.cl.prop.women25.40.M.15.25 <- d.MAR.cov.70.cl.prop.women[,2]
vector.MAR.cov.70.cl.prop.men40.50.F.15.25 <- d.MAR.cov.70.cl.prop.men[,3]
vector.MAR.cov.70.cl.prop.women40.50.M.15.25 <- d.MAR.cov.70.cl.prop.women[,3]
vector.MAR.cov.70.cl.prop.men15.25.F.25.40 <- d.MAR.cov.70.cl.prop.men[,4]
vector.MAR.cov.70.cl.prop.women15.25.M.25.40 <- d.MAR.cov.70.cl.prop.women[,4]
vector.MAR.cov.70.cl.prop.men25.40.F.25.40 <- d.MAR.cov.70.cl.prop.men[,5]
vector.MAR.cov.70.cl.prop.women25.40.M.25.40 <- d.MAR.cov.70.cl.prop.women[,5]
vector.MAR.cov.70.cl.prop.men40.50.F.25.40 <- d.MAR.cov.70.cl.prop.men[,6]
vector.MAR.cov.70.cl.prop.women40.50.M.25.40 <- d.MAR.cov.70.cl.prop.women[,6]
vector.MAR.cov.70.cl.prop.men15.25.F.40.50 <- d.MAR.cov.70.cl.prop.men[,7]
vector.MAR.cov.70.cl.prop.women15.25.M.40.50 <- d.MAR.cov.70.cl.prop.women[,7]
vector.MAR.cov.70.cl.prop.men25.40.F.40.50 <- d.MAR.cov.70.cl.prop.men[,8]
vector.MAR.cov.70.cl.prop.women25.40.M.40.50 <- d.MAR.cov.70.cl.prop.women[,8]
vector.MAR.cov.70.cl.prop.men40.50.F.40.50 <- d.MAR.cov.70.cl.prop.men[,9]
vector.MAR.cov.70.cl.prop.women40.50.M.40.50 <- d.MAR.cov.70.cl.prop.women[,9]
# Summarised
d.MAR.cov.70.cl.prop.men15.25.F.15.25 <- quant.med(d.MAR.cov.70.cl.prop.men[,1])
d.MAR.cov.70.cl.prop.women15.25.M.15.25 <- quant.med(d.MAR.cov.70.cl.prop.women[,1])
d.MAR.cov.70.cl.prop.men25.40.F.15.25 <- quant.med(d.MAR.cov.70.cl.prop.men[,2])
d.MAR.cov.70.cl.prop.women25.40.M.15.25 <- quant.med(d.MAR.cov.70.cl.prop.women[,2])
d.MAR.cov.70.cl.prop.men40.50.F.15.25 <- quant.med(d.MAR.cov.70.cl.prop.men[,3])
d.MAR.cov.70.cl.prop.women40.50.M.15.25 <- quant.med(d.MAR.cov.70.cl.prop.women[,3])
d.MAR.cov.70.cl.prop.men15.25.F.25.40 <- quant.med(d.MAR.cov.70.cl.prop.men[,4])
d.MAR.cov.70.cl.prop.women15.25.M.25.40 <- quant.med(d.MAR.cov.70.cl.prop.women[,4])
d.MAR.cov.70.cl.prop.men25.40.F.25.40 <- quant.med(d.MAR.cov.70.cl.prop.men[,5])
d.MAR.cov.70.cl.prop.women25.40.M.25.40 <- quant.med(d.MAR.cov.70.cl.prop.women[,5])
d.MAR.cov.70.cl.prop.men40.50.F.25.40 <- quant.med(d.MAR.cov.70.cl.prop.men[,6])
d.MAR.cov.70.cl.prop.women40.50.M.25.40 <- quant.med(d.MAR.cov.70.cl.prop.women[,6])
d.MAR.cov.70.cl.prop.men15.25.F.40.50 <- quant.med(d.MAR.cov.70.cl.prop.men[,7])
d.MAR.cov.70.cl.prop.women15.25.M.40.50 <- quant.med(d.MAR.cov.70.cl.prop.women[,7])
d.MAR.cov.70.cl.prop.men25.40.F.40.50 <- quant.med(d.MAR.cov.70.cl.prop.men[,8])
d.MAR.cov.70.cl.prop.women25.40.M.40.50 <- quant.med(d.MAR.cov.70.cl.prop.women[,8])
d.MAR.cov.70.cl.prop.men40.50.F.40.50 <- quant.med(d.MAR.cov.70.cl.prop.men[,9])
d.MAR.cov.70.cl.prop.women40.50.M.40.50 <- quant.med(d.MAR.cov.70.cl.prop.women[,9])
# Cov 75
# Vector
vector.MAR.cov.75.cl.prop.men15.25.F.15.25 <- d.MAR.cov.75.cl.prop.men[,1]
vector.MAR.cov.75.cl.prop.women15.25.M.15.25 <- d.MAR.cov.75.cl.prop.women[,1]
vector.MAR.cov.75.cl.prop.men25.40.F.15.25 <- d.MAR.cov.75.cl.prop.men[,2]
vector.MAR.cov.75.cl.prop.women25.40.M.15.25 <- d.MAR.cov.75.cl.prop.women[,2]
vector.MAR.cov.75.cl.prop.men40.50.F.15.25 <- d.MAR.cov.75.cl.prop.men[,3]
vector.MAR.cov.75.cl.prop.women40.50.M.15.25 <- d.MAR.cov.75.cl.prop.women[,3]
vector.MAR.cov.75.cl.prop.men15.25.F.25.40 <- d.MAR.cov.75.cl.prop.men[,4]
vector.MAR.cov.75.cl.prop.women15.25.M.25.40 <- d.MAR.cov.75.cl.prop.women[,4]
vector.MAR.cov.75.cl.prop.men25.40.F.25.40 <- d.MAR.cov.75.cl.prop.men[,5]
vector.MAR.cov.75.cl.prop.women25.40.M.25.40 <- d.MAR.cov.75.cl.prop.women[,5]
vector.MAR.cov.75.cl.prop.men40.50.F.25.40 <- d.MAR.cov.75.cl.prop.men[,6]
vector.MAR.cov.75.cl.prop.women40.50.M.25.40 <- d.MAR.cov.75.cl.prop.women[,6]
vector.MAR.cov.75.cl.prop.men15.25.F.40.50 <- d.MAR.cov.75.cl.prop.men[,7]
vector.MAR.cov.75.cl.prop.women15.25.M.40.50 <- d.MAR.cov.75.cl.prop.women[,7]
vector.MAR.cov.75.cl.prop.men25.40.F.40.50 <- d.MAR.cov.75.cl.prop.men[,8]
vector.MAR.cov.75.cl.prop.women25.40.M.40.50 <- d.MAR.cov.75.cl.prop.women[,8]
vector.MAR.cov.75.cl.prop.men40.50.F.40.50 <- d.MAR.cov.75.cl.prop.men[,9]
vector.MAR.cov.75.cl.prop.women40.50.M.40.50 <- d.MAR.cov.75.cl.prop.women[,9]
# Summarised
d.MAR.cov.75.cl.prop.men15.25.F.15.25 <- quant.med(d.MAR.cov.75.cl.prop.men[,1])
d.MAR.cov.75.cl.prop.women15.25.M.15.25 <- quant.med(d.MAR.cov.75.cl.prop.women[,1])
d.MAR.cov.75.cl.prop.men25.40.F.15.25 <- quant.med(d.MAR.cov.75.cl.prop.men[,2])
d.MAR.cov.75.cl.prop.women25.40.M.15.25 <- quant.med(d.MAR.cov.75.cl.prop.women[,2])
d.MAR.cov.75.cl.prop.men40.50.F.15.25 <- quant.med(d.MAR.cov.75.cl.prop.men[,3])
d.MAR.cov.75.cl.prop.women40.50.M.15.25 <- quant.med(d.MAR.cov.75.cl.prop.women[,3])
d.MAR.cov.75.cl.prop.men15.25.F.25.40 <- quant.med(d.MAR.cov.75.cl.prop.men[,4])
d.MAR.cov.75.cl.prop.women15.25.M.25.40 <- quant.med(d.MAR.cov.75.cl.prop.women[,4])
d.MAR.cov.75.cl.prop.men25.40.F.25.40 <- quant.med(d.MAR.cov.75.cl.prop.men[,5])
d.MAR.cov.75.cl.prop.women25.40.M.25.40 <- quant.med(d.MAR.cov.75.cl.prop.women[,5])
d.MAR.cov.75.cl.prop.men40.50.F.25.40 <- quant.med(d.MAR.cov.75.cl.prop.men[,6])
d.MAR.cov.75.cl.prop.women40.50.M.25.40 <- quant.med(d.MAR.cov.75.cl.prop.women[,6])
d.MAR.cov.75.cl.prop.men15.25.F.40.50 <- quant.med(d.MAR.cov.75.cl.prop.men[,7])
d.MAR.cov.75.cl.prop.women15.25.M.40.50 <- quant.med(d.MAR.cov.75.cl.prop.women[,7])
d.MAR.cov.75.cl.prop.men25.40.F.40.50 <- quant.med(d.MAR.cov.75.cl.prop.men[,8])
d.MAR.cov.75.cl.prop.women25.40.M.40.50 <- quant.med(d.MAR.cov.75.cl.prop.women[,8])
d.MAR.cov.75.cl.prop.men40.50.F.40.50 <- quant.med(d.MAR.cov.75.cl.prop.men[,9])
d.MAR.cov.75.cl.prop.women40.50.M.40.50 <- quant.med(d.MAR.cov.75.cl.prop.women[,9])
# Cov 80
# Vector
vector.MAR.cov.80.cl.prop.men15.25.F.15.25 <- d.MAR.cov.80.cl.prop.men[,1]
vector.MAR.cov.80.cl.prop.women15.25.M.15.25 <- d.MAR.cov.80.cl.prop.women[,1]
vector.MAR.cov.80.cl.prop.men25.40.F.15.25 <- d.MAR.cov.80.cl.prop.men[,2]
vector.MAR.cov.80.cl.prop.women25.40.M.15.25 <- d.MAR.cov.80.cl.prop.women[,2]
vector.MAR.cov.80.cl.prop.men40.50.F.15.25 <- d.MAR.cov.80.cl.prop.men[,3]
vector.MAR.cov.80.cl.prop.women40.50.M.15.25 <- d.MAR.cov.80.cl.prop.women[,3]
vector.MAR.cov.80.cl.prop.men15.25.F.25.40 <- d.MAR.cov.80.cl.prop.men[,4]
vector.MAR.cov.80.cl.prop.women15.25.M.25.40 <- d.MAR.cov.80.cl.prop.women[,4]
vector.MAR.cov.80.cl.prop.men25.40.F.25.40 <- d.MAR.cov.80.cl.prop.men[,5]
vector.MAR.cov.80.cl.prop.women25.40.M.25.40 <- d.MAR.cov.80.cl.prop.women[,5]
vector.MAR.cov.80.cl.prop.men40.50.F.25.40 <- d.MAR.cov.80.cl.prop.men[,6]
vector.MAR.cov.80.cl.prop.women40.50.M.25.40 <- d.MAR.cov.80.cl.prop.women[,6]
vector.MAR.cov.80.cl.prop.men15.25.F.40.50 <- d.MAR.cov.80.cl.prop.men[,7]
vector.MAR.cov.80.cl.prop.women15.25.M.40.50 <- d.MAR.cov.80.cl.prop.women[,7]
vector.MAR.cov.80.cl.prop.men25.40.F.40.50 <- d.MAR.cov.80.cl.prop.men[,8]
vector.MAR.cov.80.cl.prop.women25.40.M.40.50 <- d.MAR.cov.80.cl.prop.women[,8]
vector.MAR.cov.80.cl.prop.men40.50.F.40.50 <- d.MAR.cov.80.cl.prop.men[,9]
vector.MAR.cov.80.cl.prop.women40.50.M.40.50 <- d.MAR.cov.80.cl.prop.women[,9]
# Summarised
d.MAR.cov.80.cl.prop.men15.25.F.15.25 <- quant.med(d.MAR.cov.80.cl.prop.men[,1])
d.MAR.cov.80.cl.prop.women15.25.M.15.25 <- quant.med(d.MAR.cov.80.cl.prop.women[,1])
d.MAR.cov.80.cl.prop.men25.40.F.15.25 <- quant.med(d.MAR.cov.80.cl.prop.men[,2])
d.MAR.cov.80.cl.prop.women25.40.M.15.25 <- quant.med(d.MAR.cov.80.cl.prop.women[,2])
d.MAR.cov.80.cl.prop.men40.50.F.15.25 <- quant.med(d.MAR.cov.80.cl.prop.men[,3])
d.MAR.cov.80.cl.prop.women40.50.M.15.25 <- quant.med(d.MAR.cov.80.cl.prop.women[,3])
d.MAR.cov.80.cl.prop.men15.25.F.25.40 <- quant.med(d.MAR.cov.80.cl.prop.men[,4])
d.MAR.cov.80.cl.prop.women15.25.M.25.40 <- quant.med(d.MAR.cov.80.cl.prop.women[,4])
d.MAR.cov.80.cl.prop.men25.40.F.25.40 <- quant.med(d.MAR.cov.80.cl.prop.men[,5])
d.MAR.cov.80.cl.prop.women25.40.M.25.40 <- quant.med(d.MAR.cov.80.cl.prop.women[,5])
d.MAR.cov.80.cl.prop.men40.50.F.25.40 <- quant.med(d.MAR.cov.80.cl.prop.men[,6])
d.MAR.cov.80.cl.prop.women40.50.M.25.40 <- quant.med(d.MAR.cov.80.cl.prop.women[,6])
d.MAR.cov.80.cl.prop.men15.25.F.40.50 <- quant.med(d.MAR.cov.80.cl.prop.men[,7])
d.MAR.cov.80.cl.prop.women15.25.M.40.50 <- quant.med(d.MAR.cov.80.cl.prop.women[,7])
d.MAR.cov.80.cl.prop.men25.40.F.40.50 <- quant.med(d.MAR.cov.80.cl.prop.men[,8])
d.MAR.cov.80.cl.prop.women25.40.M.40.50 <- quant.med(d.MAR.cov.80.cl.prop.women[,8])
d.MAR.cov.80.cl.prop.men40.50.F.40.50 <- quant.med(d.MAR.cov.80.cl.prop.men[,9])
d.MAR.cov.80.cl.prop.women40.50.M.40.50 <- quant.med(d.MAR.cov.80.cl.prop.women[,9])
# Cov 85
# Vector
vector.MAR.cov.85.cl.prop.men15.25.F.15.25 <- d.MAR.cov.85.cl.prop.men[,1]
vector.MAR.cov.85.cl.prop.women15.25.M.15.25 <- d.MAR.cov.85.cl.prop.women[,1]
vector.MAR.cov.85.cl.prop.men25.40.F.15.25 <- d.MAR.cov.85.cl.prop.men[,2]
vector.MAR.cov.85.cl.prop.women25.40.M.15.25 <- d.MAR.cov.85.cl.prop.women[,2]
vector.MAR.cov.85.cl.prop.men40.50.F.15.25 <- d.MAR.cov.85.cl.prop.men[,3]
vector.MAR.cov.85.cl.prop.women40.50.M.15.25 <- d.MAR.cov.85.cl.prop.women[,3]
vector.MAR.cov.85.cl.prop.men15.25.F.25.40 <- d.MAR.cov.85.cl.prop.men[,4]
vector.MAR.cov.85.cl.prop.women15.25.M.25.40 <- d.MAR.cov.85.cl.prop.women[,4]
vector.MAR.cov.85.cl.prop.men25.40.F.25.40 <- d.MAR.cov.85.cl.prop.men[,5]
vector.MAR.cov.85.cl.prop.women25.40.M.25.40 <- d.MAR.cov.85.cl.prop.women[,5]
vector.MAR.cov.85.cl.prop.men40.50.F.25.40 <- d.MAR.cov.85.cl.prop.men[,6]
vector.MAR.cov.85.cl.prop.women40.50.M.25.40 <- d.MAR.cov.85.cl.prop.women[,6]
vector.MAR.cov.85.cl.prop.men15.25.F.40.50 <- d.MAR.cov.85.cl.prop.men[,7]
vector.MAR.cov.85.cl.prop.women15.25.M.40.50 <- d.MAR.cov.85.cl.prop.women[,7]
vector.MAR.cov.85.cl.prop.men25.40.F.40.50 <- d.MAR.cov.85.cl.prop.men[,8]
vector.MAR.cov.85.cl.prop.women25.40.M.40.50 <- d.MAR.cov.85.cl.prop.women[,8]
vector.MAR.cov.85.cl.prop.men40.50.F.40.50 <- d.MAR.cov.85.cl.prop.men[,9]
vector.MAR.cov.85.cl.prop.women40.50.M.40.50 <- d.MAR.cov.85.cl.prop.women[,9]
# Summarised
d.MAR.cov.85.cl.prop.men15.25.F.15.25 <- quant.med(d.MAR.cov.85.cl.prop.men[,1])
d.MAR.cov.85.cl.prop.women15.25.M.15.25 <- quant.med(d.MAR.cov.85.cl.prop.women[,1])
d.MAR.cov.85.cl.prop.men25.40.F.15.25 <- quant.med(d.MAR.cov.85.cl.prop.men[,2])
d.MAR.cov.85.cl.prop.women25.40.M.15.25 <- quant.med(d.MAR.cov.85.cl.prop.women[,2])
d.MAR.cov.85.cl.prop.men40.50.F.15.25 <- quant.med(d.MAR.cov.85.cl.prop.men[,3])
d.MAR.cov.85.cl.prop.women40.50.M.15.25 <- quant.med(d.MAR.cov.85.cl.prop.women[,3])
d.MAR.cov.85.cl.prop.men15.25.F.25.40 <- quant.med(d.MAR.cov.85.cl.prop.men[,4])
d.MAR.cov.85.cl.prop.women15.25.M.25.40 <- quant.med(d.MAR.cov.85.cl.prop.women[,4])
d.MAR.cov.85.cl.prop.men25.40.F.25.40 <- quant.med(d.MAR.cov.85.cl.prop.men[,5])
d.MAR.cov.85.cl.prop.women25.40.M.25.40 <- quant.med(d.MAR.cov.85.cl.prop.women[,5])
d.MAR.cov.85.cl.prop.men40.50.F.25.40 <- quant.med(d.MAR.cov.85.cl.prop.men[,6])
d.MAR.cov.85.cl.prop.women40.50.M.25.40 <- quant.med(d.MAR.cov.85.cl.prop.women[,6])
d.MAR.cov.85.cl.prop.men15.25.F.40.50 <- quant.med(d.MAR.cov.85.cl.prop.men[,7])
d.MAR.cov.85.cl.prop.women15.25.M.40.50 <- quant.med(d.MAR.cov.85.cl.prop.women[,7])
d.MAR.cov.85.cl.prop.men25.40.F.40.50 <- quant.med(d.MAR.cov.85.cl.prop.men[,8])
d.MAR.cov.85.cl.prop.women25.40.M.40.50 <- quant.med(d.MAR.cov.85.cl.prop.women[,8])
d.MAR.cov.85.cl.prop.men40.50.F.40.50 <- quant.med(d.MAR.cov.85.cl.prop.men[,9])
d.MAR.cov.85.cl.prop.women40.50.M.40.50 <- quant.med(d.MAR.cov.85.cl.prop.women[,9])
# Cov 90
# Vector
vector.MAR.cov.90.cl.prop.men15.25.F.15.25 <- d.MAR.cov.90.cl.prop.men[,1]
vector.MAR.cov.90.cl.prop.women15.25.M.15.25 <- d.MAR.cov.90.cl.prop.women[,1]
vector.MAR.cov.90.cl.prop.men25.40.F.15.25 <- d.MAR.cov.90.cl.prop.men[,2]
vector.MAR.cov.90.cl.prop.women25.40.M.15.25 <- d.MAR.cov.90.cl.prop.women[,2]
vector.MAR.cov.90.cl.prop.men40.50.F.15.25 <- d.MAR.cov.90.cl.prop.men[,3]
vector.MAR.cov.90.cl.prop.women40.50.M.15.25 <- d.MAR.cov.90.cl.prop.women[,3]
vector.MAR.cov.90.cl.prop.men15.25.F.25.40 <- d.MAR.cov.90.cl.prop.men[,4]
vector.MAR.cov.90.cl.prop.women15.25.M.25.40 <- d.MAR.cov.90.cl.prop.women[,4]
vector.MAR.cov.90.cl.prop.men25.40.F.25.40 <- d.MAR.cov.90.cl.prop.men[,5]
vector.MAR.cov.90.cl.prop.women25.40.M.25.40 <- d.MAR.cov.90.cl.prop.women[,5]
vector.MAR.cov.90.cl.prop.men40.50.F.25.40 <- d.MAR.cov.90.cl.prop.men[,6]
vector.MAR.cov.90.cl.prop.women40.50.M.25.40 <- d.MAR.cov.90.cl.prop.women[,6]
vector.MAR.cov.90.cl.prop.men15.25.F.40.50 <- d.MAR.cov.90.cl.prop.men[,7]
vector.MAR.cov.90.cl.prop.women15.25.M.40.50 <- d.MAR.cov.90.cl.prop.women[,7]
vector.MAR.cov.90.cl.prop.men25.40.F.40.50 <- d.MAR.cov.90.cl.prop.men[,8]
vector.MAR.cov.90.cl.prop.women25.40.M.40.50 <- d.MAR.cov.90.cl.prop.women[,8]
vector.MAR.cov.90.cl.prop.men40.50.F.40.50 <- d.MAR.cov.90.cl.prop.men[,9]
vector.MAR.cov.90.cl.prop.women40.50.M.40.50 <- d.MAR.cov.90.cl.prop.women[,9]
# Summarised
d.MAR.cov.90.cl.prop.men15.25.F.15.25 <- quant.med(d.MAR.cov.90.cl.prop.men[,1])
d.MAR.cov.90.cl.prop.women15.25.M.15.25 <- quant.med(d.MAR.cov.90.cl.prop.women[,1])
d.MAR.cov.90.cl.prop.men25.40.F.15.25 <- quant.med(d.MAR.cov.90.cl.prop.men[,2])
d.MAR.cov.90.cl.prop.women25.40.M.15.25 <- quant.med(d.MAR.cov.90.cl.prop.women[,2])
d.MAR.cov.90.cl.prop.men40.50.F.15.25 <- quant.med(d.MAR.cov.90.cl.prop.men[,3])
d.MAR.cov.90.cl.prop.women40.50.M.15.25 <- quant.med(d.MAR.cov.90.cl.prop.women[,3])
d.MAR.cov.90.cl.prop.men15.25.F.25.40 <- quant.med(d.MAR.cov.90.cl.prop.men[,4])
d.MAR.cov.90.cl.prop.women15.25.M.25.40 <- quant.med(d.MAR.cov.90.cl.prop.women[,4])
d.MAR.cov.90.cl.prop.men25.40.F.25.40 <- quant.med(d.MAR.cov.90.cl.prop.men[,5])
d.MAR.cov.90.cl.prop.women25.40.M.25.40 <- quant.med(d.MAR.cov.90.cl.prop.women[,5])
d.MAR.cov.90.cl.prop.men40.50.F.25.40 <- quant.med(d.MAR.cov.90.cl.prop.men[,6])
d.MAR.cov.90.cl.prop.women40.50.M.25.40 <- quant.med(d.MAR.cov.90.cl.prop.women[,6])
d.MAR.cov.90.cl.prop.men15.25.F.40.50 <- quant.med(d.MAR.cov.90.cl.prop.men[,7])
d.MAR.cov.90.cl.prop.women15.25.M.40.50 <- quant.med(d.MAR.cov.90.cl.prop.women[,7])
d.MAR.cov.90.cl.prop.men25.40.F.40.50 <- quant.med(d.MAR.cov.90.cl.prop.men[,8])
d.MAR.cov.90.cl.prop.women25.40.M.40.50 <- quant.med(d.MAR.cov.90.cl.prop.women[,8])
d.MAR.cov.90.cl.prop.men40.50.F.40.50 <- quant.med(d.MAR.cov.90.cl.prop.men[,9])
d.MAR.cov.90.cl.prop.women40.50.M.40.50 <- quant.med(d.MAR.cov.90.cl.prop.women[,9])
# Cov 95
# Vector
vector.MAR.cov.95.cl.prop.men15.25.F.15.25 <- d.MAR.cov.95.cl.prop.men[,1]
vector.MAR.cov.95.cl.prop.women15.25.M.15.25 <- d.MAR.cov.95.cl.prop.women[,1]
vector.MAR.cov.95.cl.prop.men25.40.F.15.25 <- d.MAR.cov.95.cl.prop.men[,2]
vector.MAR.cov.95.cl.prop.women25.40.M.15.25 <- d.MAR.cov.95.cl.prop.women[,2]
vector.MAR.cov.95.cl.prop.men40.50.F.15.25 <- d.MAR.cov.95.cl.prop.men[,3]
vector.MAR.cov.95.cl.prop.women40.50.M.15.25 <- d.MAR.cov.95.cl.prop.women[,3]
vector.MAR.cov.95.cl.prop.men15.25.F.25.40 <- d.MAR.cov.95.cl.prop.men[,4]
vector.MAR.cov.95.cl.prop.women15.25.M.25.40 <- d.MAR.cov.95.cl.prop.women[,4]
vector.MAR.cov.95.cl.prop.men25.40.F.25.40 <- d.MAR.cov.95.cl.prop.men[,5]
vector.MAR.cov.95.cl.prop.women25.40.M.25.40 <- d.MAR.cov.95.cl.prop.women[,5]
vector.MAR.cov.95.cl.prop.men40.50.F.25.40 <- d.MAR.cov.95.cl.prop.men[,6]
vector.MAR.cov.95.cl.prop.women40.50.M.25.40 <- d.MAR.cov.95.cl.prop.women[,6]
vector.MAR.cov.95.cl.prop.men15.25.F.40.50 <- d.MAR.cov.95.cl.prop.men[,7]
vector.MAR.cov.95.cl.prop.women15.25.M.40.50 <- d.MAR.cov.95.cl.prop.women[,7]
vector.MAR.cov.95.cl.prop.men25.40.F.40.50 <- d.MAR.cov.95.cl.prop.men[,8]
vector.MAR.cov.95.cl.prop.women25.40.M.40.50 <- d.MAR.cov.95.cl.prop.women[,8]
vector.MAR.cov.95.cl.prop.men40.50.F.40.50 <- d.MAR.cov.95.cl.prop.men[,9]
vector.MAR.cov.95.cl.prop.women40.50.M.40.50 <- d.MAR.cov.95.cl.prop.women[,9]
# Summarised
d.MAR.cov.95.cl.prop.men15.25.F.15.25 <- quant.med(d.MAR.cov.95.cl.prop.men[,1])
d.MAR.cov.95.cl.prop.women15.25.M.15.25 <- quant.med(d.MAR.cov.95.cl.prop.women[,1])
d.MAR.cov.95.cl.prop.men25.40.F.15.25 <- quant.med(d.MAR.cov.95.cl.prop.men[,2])
d.MAR.cov.95.cl.prop.women25.40.M.15.25 <- quant.med(d.MAR.cov.95.cl.prop.women[,2])
d.MAR.cov.95.cl.prop.men40.50.F.15.25 <- quant.med(d.MAR.cov.95.cl.prop.men[,3])
d.MAR.cov.95.cl.prop.women40.50.M.15.25 <- quant.med(d.MAR.cov.95.cl.prop.women[,3])
d.MAR.cov.95.cl.prop.men15.25.F.25.40 <- quant.med(d.MAR.cov.95.cl.prop.men[,4])
d.MAR.cov.95.cl.prop.women15.25.M.25.40 <- quant.med(d.MAR.cov.95.cl.prop.women[,4])
d.MAR.cov.95.cl.prop.men25.40.F.25.40 <- quant.med(d.MAR.cov.95.cl.prop.men[,5])
d.MAR.cov.95.cl.prop.women25.40.M.25.40 <- quant.med(d.MAR.cov.95.cl.prop.women[,5])
d.MAR.cov.95.cl.prop.men40.50.F.25.40 <- quant.med(d.MAR.cov.95.cl.prop.men[,6])
d.MAR.cov.95.cl.prop.women40.50.M.25.40 <- quant.med(d.MAR.cov.95.cl.prop.women[,6])
d.MAR.cov.95.cl.prop.men15.25.F.40.50 <- quant.med(d.MAR.cov.95.cl.prop.men[,7])
d.MAR.cov.95.cl.prop.women15.25.M.40.50 <- quant.med(d.MAR.cov.95.cl.prop.women[,7])
d.MAR.cov.95.cl.prop.men25.40.F.40.50 <- quant.med(d.MAR.cov.95.cl.prop.men[,8])
d.MAR.cov.95.cl.prop.women25.40.M.40.50 <- quant.med(d.MAR.cov.95.cl.prop.women[,8])
d.MAR.cov.95.cl.prop.men40.50.F.40.50 <- quant.med(d.MAR.cov.95.cl.prop.men[,9])
d.MAR.cov.95.cl.prop.women40.50.M.40.50 <- quant.med(d.MAR.cov.95.cl.prop.women[,9])
prop_pairings_seq_cov <- matrix(c(d.MAR.cov.35.cl.prop.men15.25.F.15.25[2], d.MAR.cov.40.cl.prop.men15.25.F.15.25[2],
d.MAR.cov.45.cl.prop.men15.25.F.15.25[2], d.MAR.cov.50.cl.prop.men15.25.F.15.25[2],
d.MAR.cov.55.cl.prop.men15.25.F.15.25[2], d.MAR.cov.60.cl.prop.men15.25.F.15.25[2],
d.MAR.cov.65.cl.prop.men15.25.F.15.25[2], d.MAR.cov.70.cl.prop.men15.25.F.15.25[2],
d.MAR.cov.75.cl.prop.men15.25.F.15.25[2], d.MAR.cov.80.cl.prop.men15.25.F.15.25[2],
d.MAR.cov.85.cl.prop.men15.25.F.15.25[2], d.MAR.cov.90.cl.prop.men15.25.F.15.25[2],
d.MAR.cov.95.cl.prop.men15.25.F.15.25[2], d.MAR.true.cov.100.prop.men15.25.F.15.25[2],
d.MAR.cov.35.cl.prop.women15.25.M.15.25[2], d.MAR.cov.40.cl.prop.women15.25.M.15.25[2],
d.MAR.cov.45.cl.prop.women15.25.M.15.25[2], d.MAR.cov.50.cl.prop.women15.25.M.15.25[2],
d.MAR.cov.55.cl.prop.women15.25.M.15.25[2], d.MAR.cov.60.cl.prop.women15.25.M.15.25[2],
d.MAR.cov.65.cl.prop.women15.25.M.15.25[2], d.MAR.cov.70.cl.prop.women15.25.M.15.25[2],
d.MAR.cov.75.cl.prop.women15.25.M.15.25[2], d.MAR.cov.80.cl.prop.women15.25.M.15.25[2],
d.MAR.cov.85.cl.prop.women15.25.M.15.25[2], d.MAR.cov.90.cl.prop.women15.25.M.15.25[2],
d.MAR.cov.95.cl.prop.women15.25.M.15.25[2], d.MAR.true.cov.100.prop.women15.25.M.15.25[2],
d.MAR.cov.35.cl.prop.men25.40.F.15.25[2], d.MAR.cov.40.cl.prop.men25.40.F.15.25[2],
d.MAR.cov.45.cl.prop.men25.40.F.15.25[2], d.MAR.cov.50.cl.prop.men25.40.F.15.25[2],
d.MAR.cov.55.cl.prop.men25.40.F.15.25[2], d.MAR.cov.60.cl.prop.men25.40.F.15.25[2],
d.MAR.cov.65.cl.prop.men25.40.F.15.25[2], d.MAR.cov.70.cl.prop.men25.40.F.15.25[2],
d.MAR.cov.75.cl.prop.men25.40.F.15.25[2], d.MAR.cov.80.cl.prop.men25.40.F.15.25[2],
d.MAR.cov.85.cl.prop.men25.40.F.15.25[2], d.MAR.cov.90.cl.prop.men25.40.F.15.25[2],
d.MAR.cov.95.cl.prop.men25.40.F.15.25[2], d.MAR.true.cov.100.prop.men25.40.F.15.25[2],
d.MAR.cov.35.cl.prop.women25.40.M.15.25[2], d.MAR.cov.40.cl.prop.women25.40.M.15.25[2],
d.MAR.cov.45.cl.prop.women25.40.M.15.25[2], d.MAR.cov.50.cl.prop.women25.40.M.15.25[2],
d.MAR.cov.55.cl.prop.women25.40.M.15.25[2], d.MAR.cov.60.cl.prop.women25.40.M.15.25[2],
d.MAR.cov.65.cl.prop.women25.40.M.15.25[2], d.MAR.cov.70.cl.prop.women25.40.M.15.25[2],
d.MAR.cov.75.cl.prop.women25.40.M.15.25[2], d.MAR.cov.80.cl.prop.women25.40.M.15.25[2],
d.MAR.cov.85.cl.prop.women25.40.M.15.25[2], d.MAR.cov.90.cl.prop.women25.40.M.15.25[2],
d.MAR.cov.95.cl.prop.women25.40.M.15.25[2], d.MAR.true.cov.100.prop.women25.40.M.15.25[2],
d.MAR.cov.35.cl.prop.men40.50.F.15.25[2], d.MAR.cov.40.cl.prop.men40.50.F.15.25[2],
d.MAR.cov.45.cl.prop.men40.50.F.15.25[2], d.MAR.cov.50.cl.prop.men40.50.F.15.25[2],
d.MAR.cov.55.cl.prop.men40.50.F.15.25[2], d.MAR.cov.60.cl.prop.men40.50.F.15.25[2],
d.MAR.cov.65.cl.prop.men40.50.F.15.25[2], d.MAR.cov.70.cl.prop.men40.50.F.15.25[2],
d.MAR.cov.75.cl.prop.men40.50.F.15.25[2], d.MAR.cov.80.cl.prop.men40.50.F.15.25[2],
d.MAR.cov.85.cl.prop.men40.50.F.15.25[2], d.MAR.cov.90.cl.prop.men40.50.F.15.25[2],
d.MAR.cov.95.cl.prop.men40.50.F.15.25[2], d.MAR.true.cov.100.prop.men40.50.F.15.25[2],
d.MAR.cov.35.cl.prop.women40.50.M.15.25[2], d.MAR.cov.40.cl.prop.women40.50.M.15.25[2],
d.MAR.cov.45.cl.prop.women40.50.M.15.25[2], d.MAR.cov.50.cl.prop.women40.50.M.15.25[2],
d.MAR.cov.55.cl.prop.women40.50.M.15.25[2], d.MAR.cov.60.cl.prop.women40.50.M.15.25[2],
d.MAR.cov.65.cl.prop.women40.50.M.15.25[2], d.MAR.cov.70.cl.prop.women40.50.M.15.25[2],
d.MAR.cov.75.cl.prop.women40.50.M.15.25[2], d.MAR.cov.80.cl.prop.women40.50.M.15.25[2],
d.MAR.cov.85.cl.prop.women40.50.M.15.25[2], d.MAR.cov.90.cl.prop.women40.50.M.15.25[2],
d.MAR.cov.95.cl.prop.women40.50.M.15.25[2], d.MAR.true.cov.100.prop.women40.50.M.15.25[2],
d.MAR.cov.35.cl.prop.men15.25.F.25.40[2], d.MAR.cov.40.cl.prop.men15.25.F.25.40[2],
d.MAR.cov.45.cl.prop.men15.25.F.25.40[2], d.MAR.cov.50.cl.prop.men15.25.F.25.40[2],
d.MAR.cov.55.cl.prop.men15.25.F.25.40[2], d.MAR.cov.60.cl.prop.men15.25.F.25.40[2],
d.MAR.cov.65.cl.prop.men15.25.F.25.40[2], d.MAR.cov.70.cl.prop.men15.25.F.25.40[2],
d.MAR.cov.75.cl.prop.men15.25.F.25.40[2], d.MAR.cov.80.cl.prop.men15.25.F.25.40[2],
d.MAR.cov.85.cl.prop.men15.25.F.25.40[2], d.MAR.cov.90.cl.prop.men15.25.F.25.40[2],
d.MAR.cov.95.cl.prop.men15.25.F.25.40[2], d.MAR.true.cov.100.prop.men15.25.F.25.40[2],
d.MAR.cov.35.cl.prop.women15.25.M.25.40[2], d.MAR.cov.40.cl.prop.women15.25.M.25.40[2],
d.MAR.cov.45.cl.prop.women15.25.M.25.40[2], d.MAR.cov.50.cl.prop.women15.25.M.25.40[2],
d.MAR.cov.55.cl.prop.women15.25.M.25.40[2], d.MAR.cov.60.cl.prop.women15.25.M.25.40[2],
d.MAR.cov.65.cl.prop.women15.25.M.25.40[2], d.MAR.cov.70.cl.prop.women15.25.M.25.40[2],
d.MAR.cov.75.cl.prop.women15.25.M.25.40[2], d.MAR.cov.80.cl.prop.women15.25.M.25.40[2],
d.MAR.cov.85.cl.prop.women15.25.M.25.40[2], d.MAR.cov.90.cl.prop.women15.25.M.25.40[2],
d.MAR.cov.95.cl.prop.women15.25.M.25.40[2], d.MAR.true.cov.100.prop.women15.25.M.25.40[2],
d.MAR.cov.35.cl.prop.men25.40.F.25.40[2], d.MAR.cov.40.cl.prop.men25.40.F.25.40[2],
d.MAR.cov.45.cl.prop.men25.40.F.25.40[2], d.MAR.cov.50.cl.prop.men25.40.F.25.40[2],
d.MAR.cov.55.cl.prop.men25.40.F.25.40[2], d.MAR.cov.60.cl.prop.men25.40.F.25.40[2],
d.MAR.cov.65.cl.prop.men25.40.F.25.40[2], d.MAR.cov.70.cl.prop.men25.40.F.25.40[2],
d.MAR.cov.75.cl.prop.men25.40.F.25.40[2], d.MAR.cov.80.cl.prop.men25.40.F.25.40[2],
d.MAR.cov.85.cl.prop.men25.40.F.25.40[2], d.MAR.cov.90.cl.prop.men25.40.F.25.40[2],
d.MAR.cov.95.cl.prop.men25.40.F.25.40[2], d.MAR.true.cov.100.prop.men25.40.F.25.40[2],
d.MAR.cov.35.cl.prop.women25.40.M.25.40[2], d.MAR.cov.40.cl.prop.women25.40.M.25.40[2],
d.MAR.cov.45.cl.prop.women25.40.M.25.40[2], d.MAR.cov.50.cl.prop.women25.40.M.25.40[2],
d.MAR.cov.55.cl.prop.women25.40.M.25.40[2], d.MAR.cov.60.cl.prop.women25.40.M.25.40[2],
d.MAR.cov.65.cl.prop.women25.40.M.25.40[2], d.MAR.cov.70.cl.prop.women25.40.M.25.40[2],
d.MAR.cov.75.cl.prop.women25.40.M.25.40[2], d.MAR.cov.80.cl.prop.women25.40.M.25.40[2],
d.MAR.cov.85.cl.prop.women25.40.M.25.40[2], d.MAR.cov.90.cl.prop.women25.40.M.25.40[2],
d.MAR.cov.95.cl.prop.women25.40.M.25.40[2], d.MAR.true.cov.100.prop.women25.40.M.25.40[2],
d.MAR.cov.35.cl.prop.men40.50.F.25.40[2], d.MAR.cov.40.cl.prop.men40.50.F.25.40[2],
d.MAR.cov.45.cl.prop.men40.50.F.25.40[2], d.MAR.cov.50.cl.prop.men40.50.F.25.40[2],
d.MAR.cov.55.cl.prop.men40.50.F.25.40[2], d.MAR.cov.60.cl.prop.men40.50.F.25.40[2],
d.MAR.cov.65.cl.prop.men40.50.F.25.40[2], d.MAR.cov.70.cl.prop.men40.50.F.25.40[2],
d.MAR.cov.75.cl.prop.men40.50.F.25.40[2], d.MAR.cov.80.cl.prop.men40.50.F.25.40[2],
d.MAR.cov.85.cl.prop.men40.50.F.25.40[2], d.MAR.cov.90.cl.prop.men40.50.F.25.40[2],
d.MAR.cov.95.cl.prop.men40.50.F.25.40[2], d.MAR.true.cov.100.prop.men40.50.F.25.40[2],
d.MAR.cov.35.cl.prop.women40.50.M.25.40[2], d.MAR.cov.40.cl.prop.women40.50.M.25.40[2],
d.MAR.cov.45.cl.prop.women40.50.M.25.40[2], d.MAR.cov.50.cl.prop.women40.50.M.25.40[2],
d.MAR.cov.55.cl.prop.women40.50.M.25.40[2], d.MAR.cov.60.cl.prop.women40.50.M.25.40[2],
d.MAR.cov.65.cl.prop.women40.50.M.25.40[2], d.MAR.cov.70.cl.prop.women40.50.M.25.40[2],
d.MAR.cov.75.cl.prop.women40.50.M.25.40[2], d.MAR.cov.80.cl.prop.women40.50.M.25.40[2],
d.MAR.cov.85.cl.prop.women40.50.M.25.40[2], d.MAR.cov.90.cl.prop.women40.50.M.25.40[2],
d.MAR.cov.95.cl.prop.women40.50.M.25.40[2], d.MAR.true.cov.100.prop.women40.50.M.25.40[2],
d.MAR.cov.35.cl.prop.men15.25.F.40.50[2], d.MAR.cov.40.cl.prop.men15.25.F.40.50[2],
d.MAR.cov.45.cl.prop.men15.25.F.40.50[2], d.MAR.cov.50.cl.prop.men15.25.F.40.50[2],
d.MAR.cov.55.cl.prop.men15.25.F.40.50[2], d.MAR.cov.60.cl.prop.men15.25.F.40.50[2],
d.MAR.cov.65.cl.prop.men15.25.F.40.50[2], d.MAR.cov.70.cl.prop.men15.25.F.40.50[2],
d.MAR.cov.75.cl.prop.men15.25.F.40.50[2], d.MAR.cov.80.cl.prop.men15.25.F.40.50[2],
d.MAR.cov.85.cl.prop.men15.25.F.40.50[2], d.MAR.cov.90.cl.prop.men15.25.F.40.50[2],
d.MAR.cov.95.cl.prop.men15.25.F.40.50[2], d.MAR.true.cov.100.prop.men15.25.F.40.50[2],
d.MAR.cov.35.cl.prop.women15.25.M.40.50[2], d.MAR.cov.40.cl.prop.women15.25.M.40.50[2],
d.MAR.cov.45.cl.prop.women15.25.M.40.50[2], d.MAR.cov.50.cl.prop.women15.25.M.40.50[2],
d.MAR.cov.55.cl.prop.women15.25.M.40.50[2], d.MAR.cov.60.cl.prop.women15.25.M.40.50[2],
d.MAR.cov.65.cl.prop.women15.25.M.40.50[2], d.MAR.cov.70.cl.prop.women15.25.M.40.50[2],
d.MAR.cov.75.cl.prop.women15.25.M.40.50[2], d.MAR.cov.80.cl.prop.women15.25.M.40.50[2],
d.MAR.cov.85.cl.prop.women15.25.M.40.50[2], d.MAR.cov.90.cl.prop.women15.25.M.40.50[2],
d.MAR.cov.95.cl.prop.women15.25.M.40.50[2], d.MAR.true.cov.100.prop.women15.25.M.40.50[2],
d.MAR.cov.35.cl.prop.men25.40.F.40.50[2], d.MAR.cov.40.cl.prop.men25.40.F.40.50[2],
d.MAR.cov.45.cl.prop.men25.40.F.40.50[2], d.MAR.cov.50.cl.prop.men25.40.F.40.50[2],
d.MAR.cov.55.cl.prop.men25.40.F.40.50[2], d.MAR.cov.60.cl.prop.men25.40.F.40.50[2],
d.MAR.cov.65.cl.prop.men25.40.F.40.50[2], d.MAR.cov.70.cl.prop.men25.40.F.40.50[2],
d.MAR.cov.75.cl.prop.men25.40.F.40.50[2], d.MAR.cov.80.cl.prop.men25.40.F.40.50[2],
d.MAR.cov.85.cl.prop.men25.40.F.40.50[2], d.MAR.cov.90.cl.prop.men25.40.F.40.50[2],
d.MAR.cov.95.cl.prop.men25.40.F.40.50[2], d.MAR.true.cov.100.prop.men25.40.F.40.50[2],
d.MAR.cov.35.cl.prop.women25.40.M.40.50[2], d.MAR.cov.40.cl.prop.women25.40.M.40.50[2],
d.MAR.cov.45.cl.prop.women25.40.M.40.50[2], d.MAR.cov.50.cl.prop.women25.40.M.40.50[2],
d.MAR.cov.55.cl.prop.women25.40.M.40.50[2], d.MAR.cov.60.cl.prop.women25.40.M.40.50[2],
d.MAR.cov.65.cl.prop.women25.40.M.40.50[2], d.MAR.cov.70.cl.prop.women25.40.M.40.50[2],
d.MAR.cov.75.cl.prop.women25.40.M.40.50[2], d.MAR.cov.80.cl.prop.women25.40.M.40.50[2],
d.MAR.cov.85.cl.prop.women25.40.M.40.50[2], d.MAR.cov.90.cl.prop.women25.40.M.40.50[2],
d.MAR.cov.95.cl.prop.women25.40.M.40.50[2], d.MAR.true.cov.100.prop.women25.40.M.40.50[2],
d.MAR.cov.35.cl.prop.men40.50.F.40.50[2], d.MAR.cov.40.cl.prop.men40.50.F.40.50[2],
d.MAR.cov.45.cl.prop.men40.50.F.40.50[2], d.MAR.cov.50.cl.prop.men40.50.F.40.50[2],
d.MAR.cov.55.cl.prop.men40.50.F.40.50[2], d.MAR.cov.60.cl.prop.men40.50.F.40.50[2],
d.MAR.cov.65.cl.prop.men40.50.F.40.50[2], d.MAR.cov.70.cl.prop.men40.50.F.40.50[2],
d.MAR.cov.75.cl.prop.men40.50.F.40.50[2], d.MAR.cov.80.cl.prop.men40.50.F.40.50[2],
d.MAR.cov.85.cl.prop.men40.50.F.40.50[2], d.MAR.cov.90.cl.prop.men40.50.F.40.50[2],
d.MAR.cov.95.cl.prop.men40.50.F.40.50[2], d.MAR.true.cov.100.prop.men40.50.F.40.50[2],
d.MAR.cov.35.cl.prop.women40.50.M.40.50[2], d.MAR.cov.40.cl.prop.women40.50.M.40.50[2],
d.MAR.cov.45.cl.prop.women40.50.M.40.50[2], d.MAR.cov.50.cl.prop.women40.50.M.40.50[2],
d.MAR.cov.55.cl.prop.women40.50.M.40.50[2], d.MAR.cov.60.cl.prop.women40.50.M.40.50[2],
d.MAR.cov.65.cl.prop.women40.50.M.40.50[2], d.MAR.cov.70.cl.prop.women40.50.M.40.50[2],
d.MAR.cov.75.cl.prop.women40.50.M.40.50[2], d.MAR.cov.80.cl.prop.women40.50.M.40.50[2],
d.MAR.cov.85.cl.prop.women40.50.M.40.50[2], d.MAR.cov.90.cl.prop.women40.50.M.40.50[2],
d.MAR.cov.95.cl.prop.women40.50.M.40.50[2], d.MAR.true.cov.100.prop.women40.50.M.40.50[2]
),
ncol = 14,
byrow = TRUE)
prop_pairings_seq_cov <- round(prop_pairings_seq_cov, digits = 3)
colnames(prop_pairings_seq_cov) <- c("35", "40", "45",
"50", "55", "60",
"65", "70", "75",
"80", "85", "90",
"95", "true_100")
rownames(prop_pairings_seq_cov) <- c("M.15.25.F.15.25", "F.15.25.M.15.25",
"M.25.40.F.15.25", "F.25.40.M.15.25",
"M.40.50.F.15.25", "F.40.50.M.15.25",
"M.15.25.F.25.40", "F.15.25.M.25.40",
"M.25.40.F.25.40", "F.25.40.M.25.40",
"M.40.50.F.25.40", "F.40.50.M.25.40",
"M.15.25.F.40.50", "F.15.25.M.40.50",
"M.25.40.F.40.50", "F.25.40.M.40.50",
"M.40.50.F.40.50", "F.40.50.M.40.50")
# prop_pairings_seq_cov %>%
# kable() %>%
# kable_styling("striped") # Commentred in OCTOBER
# Critical age groups
prop_pairings_seq_cov_target <- prop_pairings_seq_cov[-c(4, 6, 7, 12, 13, 15, 17, 18),]
prop_pairings_seq_cov_target %>%
kable() %>%
kable_styling("striped")| 35 | 40 | 45 | 50 | 55 | 60 | 65 | 70 | 75 | 80 | 85 | 90 | 95 | true_100 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| M.15.25.F.15.25 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
| F.15.25.M.15.25 | 0.286 | 0.333 | 0.333 | 0.333 | 0.333 | 0.333 | 0.316 | 0.308 | 0.294 | 0.286 | 0.265 | 0.250 | 0.259 | 0.139 |
| M.25.40.F.15.25 | 1.000 | 0.875 | 0.889 | 0.900 | 0.857 | 0.875 | 0.867 | 0.875 | 0.880 | 0.889 | 0.889 | 0.897 | 0.900 | 0.826 |
| M.40.50.F.15.25 | 0.000 | 0.000 | 0.400 | 0.500 | 0.500 | 0.500 | 0.500 | 0.545 | 0.600 | 0.600 | 0.615 | 0.600 | 0.667 | 0.519 |
| F.15.25.M.25.40 | 0.417 | 0.429 | 0.429 | 0.458 | 0.464 | 0.500 | 0.500 | 0.500 | 0.500 | 0.508 | 0.518 | 0.529 | 0.522 | 0.556 |
| M.25.40.F.25.40 | 0.000 | 0.000 | 0.000 | 0.000 | 0.091 | 0.100 | 0.125 | 0.111 | 0.118 | 0.111 | 0.111 | 0.100 | 0.100 | 0.174 |
| F.25.40.M.25.40 | 0.000 | 0.000 | 0.000 | 0.000 | 0.250 | 0.273 | 0.333 | 0.333 | 0.333 | 0.333 | 0.333 | 0.333 | 0.333 | 0.280 |
| M.40.50.F.25.40 | 0.000 | 0.000 | 0.321 | 0.286 | 0.375 | 0.400 | 0.400 | 0.400 | 0.333 | 0.375 | 0.359 | 0.389 | 0.333 | 0.478 |
| F.15.25.M.40.50 | 0.000 | 0.000 | 0.100 | 0.125 | 0.125 | 0.135 | 0.136 | 0.167 | 0.161 | 0.158 | 0.171 | 0.167 | 0.174 | 0.278 |
| F.25.40.M.40.50 | 0.000 | 0.000 | 0.293 | 0.345 | 0.429 | 0.500 | 0.500 | 0.500 | 0.500 | 0.500 | 0.500 | 0.500 | 0.500 | 0.696 |
write.csv(prop_pairings_seq_cov_target, file = "/home/david/age_mixing_patterns_phylogenetic/results/MAR_a/Table_a_14_Proportions_Pairings_at_35_95_Coverage.csv")
colnames(prop_pairings_seq_cov_target) <- c("35", "40", "45", "50", "55", "60",
"65", "70", "75", "80", "85", "90",
"95", "true_100")
v <- data.frame(matrix(ncol = 5, nrow = 0))
x <- c("cov", "val", "param", "f_m", "age_groups")
colnames(v) <- x
d <- as.data.frame(prop_pairings_seq_cov_target)
d <- d[order(row.names(d)), ]
d_f <- d
d_f$pairs <- c(rep("Females_Males", nrow(d)/2), rep("Males_Females", nrow(d)/2))
d_f$age_grp <- c(rep(c("15_24 & 15_24", "15_24 & 25_39", "15_24 & 40_49", "25_39 & 25_39", "25_39 & 40_49"), 2))
for(i in 1:length(rownames(d_f))){
cov_i <- names(d_f)[1:14]
val_i <- as.numeric(d_f[i,][1:14])
f_m_pairs_i <- rep(as.character(d_f[i,][15]), length(cov_i))
param_i <- rep(rownames(d_f[i,]), length(cov_i))
grp_i <- rep(as.character(d_f[i,][16]), length(cov_i))
v_i <- data.frame(cov_i, val_i, param_i, f_m_pairs_i, grp_i)
colnames(v_i) <- x
v <- rbind(v, v_i)
}
saveRDS(v, file = "/home/david/age_mixing_patterns_phylogenetic/results/MAR_a/MAR_a_9_Proportion_of_Pairings_at_35_95_Coverage.RDS")
plot.prop_pairings_seq_cov_target_v <- ggplot(v, aes(x=cov, y=val, colour= age_groups, group = age_groups)) +
geom_line(size=1) +
geom_point() +
facet_grid(. ~ f_m) +
# theme(legend.position="top")+
xlab("Sampling Coverage (%)") + ylab("Proportion")
print(plot.prop_pairings_seq_cov_target_v)
ggsave(filename = "Plot_a_9_Proportion_of_Pairings_at_35_95_Coverage.pdf",
plot = plot.prop_pairings_seq_cov_target_v,
path = "/home/david/age_mixing_patterns_phylogenetic/results/MAR_a",
width = 30, height = 15, units = "cm")
# "F.25.40.M.15.25", "F.40.50.M.15.25", "M.15.25.F.25.40", "F.40.50.M.25.40",
# "M.15.25.F.40.50", "M.25.40.F.40.50", "M.40.50.F.40.50", "F.40.50.M.40.50"4.3 Goodness of fit of proportions of pairings
Difference between inferred proportions of men/women from a certain age group in transmission clusters and true values of same age group proportion at 100% coverage, it shows how good is our inferrence from transmission clusters. For this purpose, we computed the Root Mean Squared Error (RMSE) of proportions of pairings in each sampling scenario:
\[\sqrt{mean[(V_{true_{100}} – V_{cov})^2]}\]
where \(V_{true_{100}}\) is a vector of true proportion values at 100%, and \(V_{cov}\) the proportion values at a given sampling scenario.
# Cov 35
# 15.25
# M.15.25.F.15.25
error.infer.clust.cov.100.men.15.25.F.15.25.cov.35 <- as.numeric(vector.MAR.true.cov.100.prop.men15.25.F.15.25) - as.numeric(vector.MAR.cov.35.cl.prop.men15.25.F.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.F.15.25.cov.35 <- RMSE(error.infer.clust.cov.100.men.15.25.F.15.25.cov.35)
MAE.error.infer.clust.cov.100.men.15.25cov.35 <- MAE(error.infer.clust.cov.100.men.15.25.F.15.25.cov.35)
ARMSE.error.infer.clust.cov.100.men.15.25cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men15.25.F.15.25, v2=vector.MAR.cov.35.cl.prop.men15.25.F.15.25)
MRE.error.infer.clust.cov.100.men.15.25.F.15.25.cov.35 <- MRE(error.infer.clust.cov.100.men.15.25.F.15.25.cov.35)
# F.15.25.M.15.25
error.infer.clust.cov.100.women.15.25.M.15.25.cov.35 <- as.numeric(vector.MAR.true.cov.100.prop.women15.25.M.15.25) - as.numeric(vector.MAR.cov.35.cl.prop.women15.25.M.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.35 <- RMSE(error.infer.clust.cov.100.women.15.25.M.15.25.cov.35)
MAE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.35 <- MAE(error.infer.clust.cov.100.women.15.25.M.15.25.cov.35)
ARMSE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women15.25.M.15.25, v2=vector.MAR.cov.35.cl.prop.women15.25.M.15.25)
MRE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.35 <- MRE(error.infer.clust.cov.100.women.15.25.M.15.25.cov.35)
# M.15.25.F.25.40
error.infer.clust.cov.100.men.15.25.F.25.40.cov.35 <- as.numeric(vector.MAR.true.cov.100.prop.men15.25.F.25.40) - as.numeric(vector.MAR.cov.35.cl.prop.men15.25.F.25.40)
RMSE.error.infer.clust.cov.100.men.15.25.F.25.40.cov.35 <- RMSE(error.infer.clust.cov.100.men.15.25.F.25.40.cov.35)
MAE.error.infer.clust.cov.100.men.15.25cov.35 <- MAE(error.infer.clust.cov.100.men.15.25.F.25.40.cov.35)
ARMSE.error.infer.clust.cov.100.men.15.25cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men15.25.F.25.40, v2=vector.MAR.cov.35.cl.prop.men15.25.F.25.40)
MRE.error.infer.clust.cov.100.men.15.25.F.25.40.cov.35 <- MRE(error.infer.clust.cov.100.men.15.25.F.25.40.cov.35)
# M.15.25.F.40.50
error.infer.clust.cov.100.men.15.25.F.40.50.cov.35 <- as.numeric(vector.MAR.true.cov.100.prop.men15.25.F.40.50) - as.numeric(vector.MAR.cov.35.cl.prop.men15.25.F.40.50)
RMSE.error.infer.clust.cov.100.men.15.25.F.40.50.cov.35 <- RMSE(error.infer.clust.cov.100.men.15.25.F.40.50.cov.35)
MAE.error.infer.clust.cov.100.men.15.25cov.35 <- MAE(error.infer.clust.cov.100.men.15.25.F.40.50.cov.35)
ARMSE.error.infer.clust.cov.100.men.15.25cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men15.25.F.40.50, v2=vector.MAR.cov.35.cl.prop.men15.25.F.40.50)
MRE.error.infer.clust.cov.100.men.15.25.F.40.50.cov.35 <- MRE(error.infer.clust.cov.100.men.15.25.F.40.50.cov.35)
# F.15.25.M.25.40
error.infer.clust.cov.100.women.15.25.M.25.40.cov.35 <- as.numeric(vector.MAR.true.cov.100.prop.women15.25.M.25.40) - as.numeric(vector.MAR.cov.35.cl.prop.women15.25.M.25.40)
RMSE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.35 <- RMSE(error.infer.clust.cov.100.women.15.25.M.25.40.cov.35)
MAE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.35 <- MAE(error.infer.clust.cov.100.women.15.25.M.25.40.cov.35)
ARMSE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women15.25.M.25.40, v2=vector.MAR.cov.35.cl.prop.women15.25.M.25.40)
MRE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.35 <- MRE(error.infer.clust.cov.100.women.15.25.M.25.40.cov.35)
# F.15.25.M.40.50
error.infer.clust.cov.100.women.15.25.M.40.50.cov.35 <- as.numeric(vector.MAR.true.cov.100.prop.women15.25.M.40.50) - as.numeric(vector.MAR.cov.35.cl.prop.women15.25.M.40.50)
RMSE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.35 <- RMSE(error.infer.clust.cov.100.women.15.25.M.40.50.cov.35)
MAE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.35 <- MAE(error.infer.clust.cov.100.women.15.25.M.40.50.cov.35)
ARMSE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women15.25.M.40.50, v2=vector.MAR.cov.35.cl.prop.women15.25.M.40.50)
MRE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.35 <- MRE(error.infer.clust.cov.100.women.15.25.M.40.50.cov.35)
# 25.40
# M.25.40.F.25.40
error.infer.clust.cov.100.men.25.40.F.25.40.cov.35 <- as.numeric(vector.MAR.true.cov.100.prop.men25.40.F.25.40) - as.numeric(vector.MAR.cov.35.cl.prop.men25.40.F.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.35 <- RMSE(error.infer.clust.cov.100.men.25.40.F.25.40.cov.35)
MAE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.35 <- MAE(error.infer.clust.cov.100.men.25.40.F.25.40.cov.35)
ARMSE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men25.40.F.25.40, v2=vector.MAR.cov.35.cl.prop.men25.40.F.25.40)
MRE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.35 <- MRE(error.infer.clust.cov.100.men.25.40.F.25.40.cov.35)
# F.25.40.M.25.40
error.infer.clust.cov.100.women.25.40.M.25.40.cov.35 <- as.numeric(vector.MAR.true.cov.100.prop.women25.40.M.25.40) - as.numeric(vector.MAR.cov.35.cl.prop.women25.40.M.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.35 <- RMSE(error.infer.clust.cov.100.women.25.40.M.25.40.cov.35)
MAE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.35 <- MAE(error.infer.clust.cov.100.women.25.40.M.25.40.cov.35)
ARMSE.error.infer.clust.cov.100.women.cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women25.40.M.25.40, v2=vector.MAR.cov.35.cl.prop.women25.40.M.25.40)
MRE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.35 <- MRE(error.infer.clust.cov.100.women.25.40.M.25.40.cov.35)
# M.25.40.F.15.25
error.infer.clust.cov.100.men.25.40.F.15.25.cov.35 <- as.numeric(vector.MAR.true.cov.100.prop.men25.40.F.15.25) - as.numeric(vector.MAR.cov.35.cl.prop.men25.40.F.15.25)
RMSE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.35 <- RMSE(error.infer.clust.cov.100.men.25.40.F.15.25.cov.35)
MAE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.35 <- MAE(error.infer.clust.cov.100.men.25.40.F.15.25.cov.35)
ARMSE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men25.40.F.15.25, v2=vector.MAR.cov.35.cl.prop.men25.40.F.15.25)
MRE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.35 <- MRE(error.infer.clust.cov.100.men.25.40.F.15.25.cov.35)
# M.25.40.F.40.50
error.infer.clust.cov.100.men.25.40.F.40.50.cov.35 <- as.numeric(vector.MAR.true.cov.100.prop.men25.40.F.40.50) - as.numeric(vector.MAR.cov.35.cl.prop.men25.40.F.40.50)
RMSE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.35 <- RMSE(error.infer.clust.cov.100.men.25.40.F.40.50.cov.35)
MAE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.35 <- MAE(error.infer.clust.cov.100.men.25.40.F.40.50.cov.35)
ARMSE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men25.40.F.40.50, v2=vector.MAR.cov.35.cl.prop.men25.40.F.40.50)
MRE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.35 <- MRE(error.infer.clust.cov.100.men.25.40.F.40.50.cov.35)
# F.25.40.M.15.25
error.infer.clust.cov.100.women.25.40.M.15.25.cov.35 <- as.numeric(vector.MAR.true.cov.100.prop.women25.40.M.15.25) - as.numeric(vector.MAR.cov.35.cl.prop.women25.40.M.15.25)
RMSE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.35 <- RMSE(error.infer.clust.cov.100.women.25.40.M.15.25.cov.35)
MAE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.35 <- MAE(error.infer.clust.cov.100.women.25.40.M.15.25.cov.35)
ARMSE.error.infer.clust.cov.100.women.cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women25.40.M.15.25, v2=vector.MAR.cov.35.cl.prop.women25.40.M.15.25)
MRE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.35 <- MRE(error.infer.clust.cov.100.women.25.40.M.15.25.cov.35)
# F.25.40.M.40.50
error.infer.clust.cov.100.women.25.40.M.40.50.cov.35 <- as.numeric(vector.MAR.true.cov.100.prop.women25.40.M.40.50) - as.numeric(vector.MAR.cov.35.cl.prop.women25.40.M.40.50)
RMSE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.35 <- RMSE(error.infer.clust.cov.100.women.25.40.M.40.50.cov.35)
MAE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.35 <- MAE(error.infer.clust.cov.100.women.25.40.M.40.50.cov.35)
ARMSE.error.infer.clust.cov.100.women.cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women25.40.M.40.50, v2=vector.MAR.cov.35.cl.prop.women25.40.M.40.50)
MRE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.35 <- MRE(error.infer.clust.cov.100.women.25.40.M.40.50.cov.35)
# 40.50
# M.40.50.F.40.50
error.infer.clust.cov.100.men.40.50.F.40.50.cov.35 <- as.numeric(vector.MAR.true.cov.100.prop.men40.50.F.40.50) - as.numeric(vector.MAR.cov.35.cl.prop.men40.50.F.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.35 <- RMSE(error.infer.clust.cov.100.men.40.50.F.40.50.cov.35)
MAE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.35 <- MAE(error.infer.clust.cov.100.men.40.50.F.40.50.cov.35)
ARMSE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men40.50.F.40.50, v2=vector.MAR.cov.35.cl.prop.men40.50.F.40.50)
MRE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.35 <- MRE(error.infer.clust.cov.100.men.40.50.F.40.50.cov.35)
# F.40.50.M.40.50
error.infer.clust.cov.100.women.40.50.M.40.50.cov.35 <- as.numeric(vector.MAR.true.cov.100.prop.women40.50.M.40.50) - as.numeric(vector.MAR.cov.35.cl.prop.women40.50.M.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.35 <- RMSE(error.infer.clust.cov.100.women.40.50.M.40.50.cov.35)
MAE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.35 <- MAE(error.infer.clust.cov.100.women.40.50.M.40.50.cov.35)
ARMSE.error.infer.clust.cov.100.women.cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women40.50.M.40.50, v2=vector.MAR.cov.35.cl.prop.women40.50.M.40.50)
MRE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.35 <- MRE(error.infer.clust.cov.100.women.40.50.M.40.50.cov.35)
# M.40.50.F.15.25
error.infer.clust.cov.100.men.40.50.F.15.25.cov.35 <- as.numeric(vector.MAR.true.cov.100.prop.men40.50.F.15.25) - as.numeric(vector.MAR.cov.35.cl.prop.men40.50.F.15.25)
RMSE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.35 <- RMSE(error.infer.clust.cov.100.men.40.50.F.15.25.cov.35)
MAE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.35 <- MAE(error.infer.clust.cov.100.men.40.50.F.15.25.cov.35)
ARMSE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men40.50.F.15.25, v2=vector.MAR.cov.35.cl.prop.men40.50.F.15.25)
MRE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.35 <- MRE(error.infer.clust.cov.100.men.40.50.F.15.25.cov.35)
# M.40.50.F.25.40
error.infer.clust.cov.100.men.40.50.F.25.40.cov.35 <- as.numeric(vector.MAR.true.cov.100.prop.men40.50.F.25.40) - as.numeric(vector.MAR.cov.35.cl.prop.men40.50.F.25.40)
RMSE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.35 <- RMSE(error.infer.clust.cov.100.men.40.50.F.25.40.cov.35)
MAE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.35 <- MAE(error.infer.clust.cov.100.men.40.50.F.25.40.cov.35)
ARMSE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men40.50.F.25.40, v2=vector.MAR.cov.35.cl.prop.men40.50.F.25.40)
MRE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.35 <- MRE(error.infer.clust.cov.100.men.40.50.F.25.40.cov.35)
# F.40.50.M.15.25
error.infer.clust.cov.100.women.40.50.M.15.25.cov.35 <- as.numeric(vector.MAR.true.cov.100.prop.women40.50.M.15.25) - as.numeric(vector.MAR.cov.35.cl.prop.women40.50.M.15.25)
RMSE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.35 <- RMSE(error.infer.clust.cov.100.women.40.50.M.15.25.cov.35)
MAE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.35 <- MAE(error.infer.clust.cov.100.women.40.50.M.15.25.cov.35)
ARMSE.error.infer.clust.cov.100.women.cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women40.50.M.15.25, v2=vector.MAR.cov.35.cl.prop.women40.50.M.15.25)
MRE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.35 <- MRE(error.infer.clust.cov.100.women.40.50.M.15.25.cov.35)
# F.40.50.M.25.40
error.infer.clust.cov.100.women.40.50.M.25.40.cov.35 <- as.numeric(vector.MAR.true.cov.100.prop.women40.50.M.25.40) - as.numeric(vector.MAR.cov.35.cl.prop.women40.50.M.25.40)
RMSE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.35 <- RMSE(error.infer.clust.cov.100.women.40.50.M.25.40.cov.35)
MAE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.35 <- MAE(error.infer.clust.cov.100.women.40.50.M.25.40.cov.35)
ARMSE.error.infer.clust.cov.100.women.cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women40.50.M.25.40, v2=vector.MAR.cov.35.cl.prop.women40.50.M.25.40)
MRE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.35 <- MRE(error.infer.clust.cov.100.women.40.50.M.25.40.cov.35)
# Cov 40
# 15.25
# M.15.25.F.15.25
error.infer.clust.cov.100.men.15.25.F.15.25.cov.40 <- as.numeric(vector.MAR.true.cov.100.prop.men15.25.F.15.25) - as.numeric(vector.MAR.cov.40.cl.prop.men15.25.F.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.F.15.25.cov.40 <- RMSE(error.infer.clust.cov.100.men.15.25.F.15.25.cov.40)
MAE.error.infer.clust.cov.100.men.15.25cov.35 <- MAE(error.infer.clust.cov.100.men.15.25.F.15.25.cov.40)
ARMSE.error.infer.clust.cov.100.men.15.25cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men15.25.F.15.25, v2=vector.MAR.cov.40.cl.prop.men15.25.F.15.25)
MRE.error.infer.clust.cov.100.men.15.25.F.15.25.cov.40 <- MRE(error.infer.clust.cov.100.men.15.25.F.15.25.cov.40)
# F.15.25.M.15.25
error.infer.clust.cov.100.women.15.25.M.15.25.cov.40 <- as.numeric(vector.MAR.true.cov.100.prop.women15.25.M.15.25) - as.numeric(vector.MAR.cov.40.cl.prop.women15.25.M.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.40 <- RMSE(error.infer.clust.cov.100.women.15.25.M.15.25.cov.40)
MAE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.40 <- MAE(error.infer.clust.cov.100.women.15.25.M.15.25.cov.40)
ARMSE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.40 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women15.25.M.15.25, v2=vector.MAR.cov.40.cl.prop.women15.25.M.15.25)
MRE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.40 <- MRE(error.infer.clust.cov.100.women.15.25.M.15.25.cov.40)
# M.15.25.F.25.40
error.infer.clust.cov.100.men.15.25.F.25.40.cov.40 <- as.numeric(vector.MAR.true.cov.100.prop.men15.25.F.25.40) - as.numeric(vector.MAR.cov.40.cl.prop.men15.25.F.25.40)
RMSE.error.infer.clust.cov.100.men.15.25.F.25.40.cov.40 <- RMSE(error.infer.clust.cov.100.men.15.25.F.25.40.cov.40)
MAE.error.infer.clust.cov.100.men.15.25cov.35 <- MAE(error.infer.clust.cov.100.men.15.25.F.25.40.cov.40)
ARMSE.error.infer.clust.cov.100.men.15.25cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men15.25.F.25.40, v2=vector.MAR.cov.40.cl.prop.men15.25.F.25.40)
MRE.error.infer.clust.cov.100.men.15.25.F.25.40.cov.40 <- MRE(error.infer.clust.cov.100.men.15.25.F.25.40.cov.40)
# M.15.25.F.40.50
error.infer.clust.cov.100.men.15.25.F.40.50.cov.40 <- as.numeric(vector.MAR.true.cov.100.prop.men15.25.F.40.50) - as.numeric(vector.MAR.cov.40.cl.prop.men15.25.F.40.50)
RMSE.error.infer.clust.cov.100.men.15.25.F.40.50.cov.40 <- RMSE(error.infer.clust.cov.100.men.15.25.F.40.50.cov.40)
MAE.error.infer.clust.cov.100.men.15.25cov.35 <- MAE(error.infer.clust.cov.100.men.15.25.F.40.50.cov.40)
ARMSE.error.infer.clust.cov.100.men.15.25cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men15.25.F.40.50, v2=vector.MAR.cov.40.cl.prop.men15.25.F.40.50)
MRE.error.infer.clust.cov.100.men.15.25.F.40.50.cov.40 <- MRE(error.infer.clust.cov.100.men.15.25.F.40.50.cov.40)
# F.15.25.M.25.40
error.infer.clust.cov.100.women.15.25.M.25.40.cov.40 <- as.numeric(vector.MAR.true.cov.100.prop.women15.25.M.25.40) - as.numeric(vector.MAR.cov.40.cl.prop.women15.25.M.25.40)
RMSE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.40 <- RMSE(error.infer.clust.cov.100.women.15.25.M.25.40.cov.40)
MAE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.40 <- MAE(error.infer.clust.cov.100.women.15.25.M.25.40.cov.40)
ARMSE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.40 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women15.25.M.25.40, v2=vector.MAR.cov.40.cl.prop.women15.25.M.25.40)
MRE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.40 <- MRE(error.infer.clust.cov.100.women.15.25.M.25.40.cov.40)
# F.15.25.M.40.50
error.infer.clust.cov.100.women.15.25.M.40.50.cov.40 <- as.numeric(vector.MAR.true.cov.100.prop.women15.25.M.40.50) - as.numeric(vector.MAR.cov.40.cl.prop.women15.25.M.40.50)
RMSE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.40 <- RMSE(error.infer.clust.cov.100.women.15.25.M.40.50.cov.40)
MAE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.40 <- MAE(error.infer.clust.cov.100.women.15.25.M.40.50.cov.40)
ARMSE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.40 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women15.25.M.40.50, v2=vector.MAR.cov.40.cl.prop.women15.25.M.40.50)
MRE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.40 <- MRE(error.infer.clust.cov.100.women.15.25.M.40.50.cov.40)
# 25.40
# M.25.40.F.25.40
error.infer.clust.cov.100.men.25.40.F.25.40.cov.40 <- as.numeric(vector.MAR.true.cov.100.prop.men25.40.F.25.40) - as.numeric(vector.MAR.cov.40.cl.prop.men25.40.F.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.40 <- RMSE(error.infer.clust.cov.100.men.25.40.F.25.40.cov.40)
MAE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.40 <- MAE(error.infer.clust.cov.100.men.25.40.F.25.40.cov.40)
ARMSE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.40 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men25.40.F.25.40, v2=vector.MAR.cov.40.cl.prop.men25.40.F.25.40)
MRE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.40 <- MRE(error.infer.clust.cov.100.men.25.40.F.25.40.cov.40)
# F.25.40.M.25.40
error.infer.clust.cov.100.women.25.40.M.25.40.cov.40 <- as.numeric(vector.MAR.true.cov.100.prop.women25.40.M.25.40) - as.numeric(vector.MAR.cov.40.cl.prop.women25.40.M.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.40 <- RMSE(error.infer.clust.cov.100.women.25.40.M.25.40.cov.40)
MAE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.40 <- MAE(error.infer.clust.cov.100.women.25.40.M.25.40.cov.40)
ARMSE.error.infer.clust.cov.100.women.cov.40 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women25.40.M.25.40, v2=vector.MAR.cov.40.cl.prop.women25.40.M.25.40)
MRE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.40 <- MRE(error.infer.clust.cov.100.women.25.40.M.25.40.cov.40)
# M.25.40.F.15.25
error.infer.clust.cov.100.men.25.40.F.15.25.cov.40 <- as.numeric(vector.MAR.true.cov.100.prop.men25.40.F.15.25) - as.numeric(vector.MAR.cov.40.cl.prop.men25.40.F.15.25)
RMSE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.40 <- RMSE(error.infer.clust.cov.100.men.25.40.F.15.25.cov.40)
MAE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.40 <- MAE(error.infer.clust.cov.100.men.25.40.F.15.25.cov.40)
ARMSE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.40 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men25.40.F.15.25, v2=vector.MAR.cov.40.cl.prop.men25.40.F.15.25)
MRE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.40 <- MRE(error.infer.clust.cov.100.men.25.40.F.15.25.cov.40)
# M.25.40.F.40.50
error.infer.clust.cov.100.men.25.40.F.40.50.cov.40 <- as.numeric(vector.MAR.true.cov.100.prop.men25.40.F.40.50) - as.numeric(vector.MAR.cov.40.cl.prop.men25.40.F.40.50)
RMSE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.40 <- RMSE(error.infer.clust.cov.100.men.25.40.F.40.50.cov.40)
MAE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.40 <- MAE(error.infer.clust.cov.100.men.25.40.F.40.50.cov.40)
ARMSE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.40 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men25.40.F.40.50, v2=vector.MAR.cov.40.cl.prop.men25.40.F.40.50)
MRE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.40 <- MRE(error.infer.clust.cov.100.men.25.40.F.40.50.cov.40)
# F.25.40.M.15.25
error.infer.clust.cov.100.women.25.40.M.15.25.cov.40 <- as.numeric(vector.MAR.true.cov.100.prop.women25.40.M.15.25) - as.numeric(vector.MAR.cov.40.cl.prop.women25.40.M.15.25)
RMSE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.40 <- RMSE(error.infer.clust.cov.100.women.25.40.M.15.25.cov.40)
MAE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.40 <- MAE(error.infer.clust.cov.100.women.25.40.M.15.25.cov.40)
ARMSE.error.infer.clust.cov.100.women.cov.40 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women25.40.M.15.25, v2=vector.MAR.cov.40.cl.prop.women25.40.M.15.25)
MRE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.40 <- MRE(error.infer.clust.cov.100.women.25.40.M.15.25.cov.40)
# F.25.40.M.40.50
error.infer.clust.cov.100.women.25.40.M.40.50.cov.40 <- as.numeric(vector.MAR.true.cov.100.prop.women25.40.M.40.50) - as.numeric(vector.MAR.cov.40.cl.prop.women25.40.M.40.50)
RMSE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.40 <- RMSE(error.infer.clust.cov.100.women.25.40.M.40.50.cov.40)
MAE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.40 <- MAE(error.infer.clust.cov.100.women.25.40.M.40.50.cov.40)
ARMSE.error.infer.clust.cov.100.women.cov.40 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women25.40.M.40.50, v2=vector.MAR.cov.40.cl.prop.women25.40.M.40.50)
MRE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.40 <- MRE(error.infer.clust.cov.100.women.25.40.M.40.50.cov.40)
# 40.50
# M.40.50.F.40.50
error.infer.clust.cov.100.men.40.50.F.40.50.cov.40 <- as.numeric(vector.MAR.true.cov.100.prop.men40.50.F.40.50) - as.numeric(vector.MAR.cov.40.cl.prop.men40.50.F.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.40 <- RMSE(error.infer.clust.cov.100.men.40.50.F.40.50.cov.40)
MAE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.40 <- MAE(error.infer.clust.cov.100.men.40.50.F.40.50.cov.40)
ARMSE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.40 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men40.50.F.40.50, v2=vector.MAR.cov.40.cl.prop.men40.50.F.40.50)
MRE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.40 <- MRE(error.infer.clust.cov.100.men.40.50.F.40.50.cov.40)
# F.40.50.M.40.50
error.infer.clust.cov.100.women.40.50.M.40.50.cov.40 <- as.numeric(vector.MAR.true.cov.100.prop.women40.50.M.40.50) - as.numeric(vector.MAR.cov.40.cl.prop.women40.50.M.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.40 <- RMSE(error.infer.clust.cov.100.women.40.50.M.40.50.cov.40)
MAE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.40 <- MAE(error.infer.clust.cov.100.women.40.50.M.40.50.cov.40)
ARMSE.error.infer.clust.cov.100.women.cov.40 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women40.50.M.40.50, v2=vector.MAR.cov.40.cl.prop.women40.50.M.40.50)
MRE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.40 <- MRE(error.infer.clust.cov.100.women.40.50.M.40.50.cov.40)
# M.40.50.F.15.25
error.infer.clust.cov.100.men.40.50.F.15.25.cov.40 <- as.numeric(vector.MAR.true.cov.100.prop.men40.50.F.15.25) - as.numeric(vector.MAR.cov.40.cl.prop.men40.50.F.15.25)
RMSE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.40 <- RMSE(error.infer.clust.cov.100.men.40.50.F.15.25.cov.40)
MAE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.40 <- MAE(error.infer.clust.cov.100.men.40.50.F.15.25.cov.40)
ARMSE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.40 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men40.50.F.15.25, v2=vector.MAR.cov.40.cl.prop.men40.50.F.15.25)
MRE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.40 <- MRE(error.infer.clust.cov.100.men.40.50.F.15.25.cov.40)
# M.40.50.F.25.40
error.infer.clust.cov.100.men.40.50.F.25.40.cov.40 <- as.numeric(vector.MAR.true.cov.100.prop.men40.50.F.25.40) - as.numeric(vector.MAR.cov.40.cl.prop.men40.50.F.25.40)
RMSE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.40 <- RMSE(error.infer.clust.cov.100.men.40.50.F.25.40.cov.40)
MAE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.40 <- MAE(error.infer.clust.cov.100.men.40.50.F.25.40.cov.40)
ARMSE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.40 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men40.50.F.25.40, v2=vector.MAR.cov.40.cl.prop.men40.50.F.25.40)
MRE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.40 <- MRE(error.infer.clust.cov.100.men.40.50.F.25.40.cov.40)
# F.40.50.M.15.25
error.infer.clust.cov.100.women.40.50.M.15.25.cov.40 <- as.numeric(vector.MAR.true.cov.100.prop.women40.50.M.15.25) - as.numeric(vector.MAR.cov.40.cl.prop.women40.50.M.15.25)
RMSE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.40 <- RMSE(error.infer.clust.cov.100.women.40.50.M.15.25.cov.40)
MAE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.40 <- MAE(error.infer.clust.cov.100.women.40.50.M.15.25.cov.40)
ARMSE.error.infer.clust.cov.100.women.cov.40 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women40.50.M.15.25, v2=vector.MAR.cov.40.cl.prop.women40.50.M.15.25)
MRE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.40 <- MRE(error.infer.clust.cov.100.women.40.50.M.15.25.cov.40)
# F.40.50.M.25.40
error.infer.clust.cov.100.women.40.50.M.25.40.cov.40 <- as.numeric(vector.MAR.true.cov.100.prop.women40.50.M.25.40) - as.numeric(vector.MAR.cov.40.cl.prop.women40.50.M.25.40)
RMSE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.40 <- RMSE(error.infer.clust.cov.100.women.40.50.M.25.40.cov.40)
MAE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.40 <- MAE(error.infer.clust.cov.100.women.40.50.M.25.40.cov.40)
ARMSE.error.infer.clust.cov.100.women.cov.40 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women40.50.M.25.40, v2=vector.MAR.cov.40.cl.prop.women40.50.M.25.40)
MRE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.40 <- MRE(error.infer.clust.cov.100.women.40.50.M.25.40.cov.40)
# Cov 45
# 15.25
# M.15.25.F.15.25
error.infer.clust.cov.100.men.15.25.F.15.25.cov.45 <- as.numeric(vector.MAR.true.cov.100.prop.men15.25.F.15.25) - as.numeric(vector.MAR.cov.45.cl.prop.men15.25.F.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.F.15.25.cov.45 <- RMSE(error.infer.clust.cov.100.men.15.25.F.15.25.cov.45)
MAE.error.infer.clust.cov.100.men.15.25cov.35 <- MAE(error.infer.clust.cov.100.men.15.25.F.15.25.cov.45)
ARMSE.error.infer.clust.cov.100.men.15.25cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men15.25.F.15.25, v2=vector.MAR.cov.45.cl.prop.men15.25.F.15.25)
MRE.error.infer.clust.cov.100.men.15.25.F.15.25.cov.45 <- MRE(error.infer.clust.cov.100.men.15.25.F.15.25.cov.45)
# F.15.25.M.15.25
error.infer.clust.cov.100.women.15.25.M.15.25.cov.45 <- as.numeric(vector.MAR.true.cov.100.prop.women15.25.M.15.25) - as.numeric(vector.MAR.cov.45.cl.prop.women15.25.M.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.45 <- RMSE(error.infer.clust.cov.100.women.15.25.M.15.25.cov.45)
MAE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.45 <- MAE(error.infer.clust.cov.100.women.15.25.M.15.25.cov.45)
ARMSE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.45 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women15.25.M.15.25, v2=vector.MAR.cov.45.cl.prop.women15.25.M.15.25)
MRE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.45 <- MRE(error.infer.clust.cov.100.women.15.25.M.15.25.cov.45)
# M.15.25.F.25.40
error.infer.clust.cov.100.men.15.25.F.25.40.cov.45 <- as.numeric(vector.MAR.true.cov.100.prop.men15.25.F.25.40) - as.numeric(vector.MAR.cov.45.cl.prop.men15.25.F.25.40)
RMSE.error.infer.clust.cov.100.men.15.25.F.25.40.cov.45 <- RMSE(error.infer.clust.cov.100.men.15.25.F.25.40.cov.45)
MAE.error.infer.clust.cov.100.men.15.25cov.35 <- MAE(error.infer.clust.cov.100.men.15.25.F.25.40.cov.45)
ARMSE.error.infer.clust.cov.100.men.15.25cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men15.25.F.25.40, v2=vector.MAR.cov.45.cl.prop.men15.25.F.25.40)
MRE.error.infer.clust.cov.100.men.15.25.F.25.40.cov.45 <- MRE(error.infer.clust.cov.100.men.15.25.F.25.40.cov.45)
# M.15.25.F.40.50
error.infer.clust.cov.100.men.15.25.F.40.50.cov.45 <- as.numeric(vector.MAR.true.cov.100.prop.men15.25.F.40.50) - as.numeric(vector.MAR.cov.45.cl.prop.men15.25.F.40.50)
RMSE.error.infer.clust.cov.100.men.15.25.F.40.50.cov.45 <- RMSE(error.infer.clust.cov.100.men.15.25.F.40.50.cov.45)
MAE.error.infer.clust.cov.100.men.15.25cov.35 <- MAE(error.infer.clust.cov.100.men.15.25.F.40.50.cov.45)
ARMSE.error.infer.clust.cov.100.men.15.25cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men15.25.F.40.50, v2=vector.MAR.cov.45.cl.prop.men15.25.F.40.50)
MRE.error.infer.clust.cov.100.men.15.25.F.40.50.cov.45 <- MRE(error.infer.clust.cov.100.men.15.25.F.40.50.cov.45)
# F.15.25.M.25.40
error.infer.clust.cov.100.women.15.25.M.25.40.cov.45 <- as.numeric(vector.MAR.true.cov.100.prop.women15.25.M.25.40) - as.numeric(vector.MAR.cov.45.cl.prop.women15.25.M.25.40)
RMSE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.45 <- RMSE(error.infer.clust.cov.100.women.15.25.M.25.40.cov.45)
MAE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.45 <- MAE(error.infer.clust.cov.100.women.15.25.M.25.40.cov.45)
ARMSE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.45 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women15.25.M.25.40, v2=vector.MAR.cov.45.cl.prop.women15.25.M.25.40)
MRE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.45 <- MRE(error.infer.clust.cov.100.women.15.25.M.25.40.cov.45)
# F.15.25.M.40.50
error.infer.clust.cov.100.women.15.25.M.40.50.cov.45 <- as.numeric(vector.MAR.true.cov.100.prop.women15.25.M.40.50) - as.numeric(vector.MAR.cov.45.cl.prop.women15.25.M.40.50)
RMSE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.45 <- RMSE(error.infer.clust.cov.100.women.15.25.M.40.50.cov.45)
MAE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.45 <- MAE(error.infer.clust.cov.100.women.15.25.M.40.50.cov.45)
ARMSE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.45 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women15.25.M.40.50, v2=vector.MAR.cov.45.cl.prop.women15.25.M.40.50)
MRE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.45 <- MRE(error.infer.clust.cov.100.women.15.25.M.40.50.cov.45)
# 25.40
# M.25.40.F.25.40
error.infer.clust.cov.100.men.25.40.F.25.40.cov.45 <- as.numeric(vector.MAR.true.cov.100.prop.men25.40.F.25.40) - as.numeric(vector.MAR.cov.45.cl.prop.men25.40.F.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.45 <- RMSE(error.infer.clust.cov.100.men.25.40.F.25.40.cov.45)
MAE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.45 <- MAE(error.infer.clust.cov.100.men.25.40.F.25.40.cov.45)
ARMSE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.45 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men25.40.F.25.40, v2=vector.MAR.cov.45.cl.prop.men25.40.F.25.40)
MRE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.45 <- MRE(error.infer.clust.cov.100.men.25.40.F.25.40.cov.45)
# F.25.40.M.25.40
error.infer.clust.cov.100.women.25.40.M.25.40.cov.45 <- as.numeric(vector.MAR.true.cov.100.prop.women25.40.M.25.40) - as.numeric(vector.MAR.cov.45.cl.prop.women25.40.M.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.45 <- RMSE(error.infer.clust.cov.100.women.25.40.M.25.40.cov.45)
MAE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.45 <- MAE(error.infer.clust.cov.100.women.25.40.M.25.40.cov.45)
ARMSE.error.infer.clust.cov.100.women.cov.45 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women25.40.M.25.40, v2=vector.MAR.cov.45.cl.prop.women25.40.M.25.40)
MRE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.45 <- MRE(error.infer.clust.cov.100.women.25.40.M.25.40.cov.45)
# M.25.40.F.15.25
error.infer.clust.cov.100.men.25.40.F.15.25.cov.45 <- as.numeric(vector.MAR.true.cov.100.prop.men25.40.F.15.25) - as.numeric(vector.MAR.cov.45.cl.prop.men25.40.F.15.25)
RMSE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.45 <- RMSE(error.infer.clust.cov.100.men.25.40.F.15.25.cov.45)
MAE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.45 <- MAE(error.infer.clust.cov.100.men.25.40.F.15.25.cov.45)
ARMSE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.45 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men25.40.F.15.25, v2=vector.MAR.cov.45.cl.prop.men25.40.F.15.25)
MRE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.45 <- MRE(error.infer.clust.cov.100.men.25.40.F.15.25.cov.45)
# M.25.40.F.40.50
error.infer.clust.cov.100.men.25.40.F.40.50.cov.45 <- as.numeric(vector.MAR.true.cov.100.prop.men25.40.F.40.50) - as.numeric(vector.MAR.cov.45.cl.prop.men25.40.F.40.50)
RMSE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.45 <- RMSE(error.infer.clust.cov.100.men.25.40.F.40.50.cov.45)
MAE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.45 <- MAE(error.infer.clust.cov.100.men.25.40.F.40.50.cov.45)
ARMSE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.45 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men25.40.F.40.50, v2=vector.MAR.cov.45.cl.prop.men25.40.F.40.50)
MRE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.45 <- MRE(error.infer.clust.cov.100.men.25.40.F.40.50.cov.45)
# F.25.40.M.15.25
error.infer.clust.cov.100.women.25.40.M.15.25.cov.45 <- as.numeric(vector.MAR.true.cov.100.prop.women25.40.M.15.25) - as.numeric(vector.MAR.cov.45.cl.prop.women25.40.M.15.25)
RMSE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.45 <- RMSE(error.infer.clust.cov.100.women.25.40.M.15.25.cov.45)
MAE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.45 <- MAE(error.infer.clust.cov.100.women.25.40.M.15.25.cov.45)
ARMSE.error.infer.clust.cov.100.women.cov.45 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women25.40.M.15.25, v2=vector.MAR.cov.45.cl.prop.women25.40.M.15.25)
MRE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.45 <- MRE(error.infer.clust.cov.100.women.25.40.M.15.25.cov.45)
# F.25.40.M.40.50
error.infer.clust.cov.100.women.25.40.M.40.50.cov.45 <- as.numeric(vector.MAR.true.cov.100.prop.women25.40.M.40.50) - as.numeric(vector.MAR.cov.45.cl.prop.women25.40.M.40.50)
RMSE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.45 <- RMSE(error.infer.clust.cov.100.women.25.40.M.40.50.cov.45)
MAE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.45 <- MAE(error.infer.clust.cov.100.women.25.40.M.40.50.cov.45)
ARMSE.error.infer.clust.cov.100.women.cov.45 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women25.40.M.40.50, v2=vector.MAR.cov.45.cl.prop.women25.40.M.40.50)
MRE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.45 <- MRE(error.infer.clust.cov.100.women.25.40.M.40.50.cov.45)
# 40.50
# M.40.50.F.40.50
error.infer.clust.cov.100.men.40.50.F.40.50.cov.45 <- as.numeric(vector.MAR.true.cov.100.prop.men40.50.F.40.50) - as.numeric(vector.MAR.cov.45.cl.prop.men40.50.F.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.45 <- RMSE(error.infer.clust.cov.100.men.40.50.F.40.50.cov.45)
MAE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.45 <- MAE(error.infer.clust.cov.100.men.40.50.F.40.50.cov.45)
ARMSE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.45 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men40.50.F.40.50, v2=vector.MAR.cov.45.cl.prop.men40.50.F.40.50)
MRE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.45 <- MRE(error.infer.clust.cov.100.men.40.50.F.40.50.cov.45)
# F.40.50.M.40.50
error.infer.clust.cov.100.women.40.50.M.40.50.cov.45 <- as.numeric(vector.MAR.true.cov.100.prop.women40.50.M.40.50) - as.numeric(vector.MAR.cov.45.cl.prop.women40.50.M.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.45 <- RMSE(error.infer.clust.cov.100.women.40.50.M.40.50.cov.45)
MAE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.45 <- MAE(error.infer.clust.cov.100.women.40.50.M.40.50.cov.45)
ARMSE.error.infer.clust.cov.100.women.cov.45 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women40.50.M.40.50, v2=vector.MAR.cov.45.cl.prop.women40.50.M.40.50)
MRE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.45 <- MRE(error.infer.clust.cov.100.women.40.50.M.40.50.cov.45)
# M.40.50.F.15.25
error.infer.clust.cov.100.men.40.50.F.15.25.cov.45 <- as.numeric(vector.MAR.true.cov.100.prop.men40.50.F.15.25) - as.numeric(vector.MAR.cov.45.cl.prop.men40.50.F.15.25)
RMSE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.45 <- RMSE(error.infer.clust.cov.100.men.40.50.F.15.25.cov.45)
MAE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.45 <- MAE(error.infer.clust.cov.100.men.40.50.F.15.25.cov.45)
ARMSE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.45 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men40.50.F.15.25, v2=vector.MAR.cov.45.cl.prop.men40.50.F.15.25)
MRE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.45 <- MRE(error.infer.clust.cov.100.men.40.50.F.15.25.cov.45)
# M.40.50.F.25.40
error.infer.clust.cov.100.men.40.50.F.25.40.cov.45 <- as.numeric(vector.MAR.true.cov.100.prop.men40.50.F.25.40) - as.numeric(vector.MAR.cov.45.cl.prop.men40.50.F.25.40)
RMSE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.45 <- RMSE(error.infer.clust.cov.100.men.40.50.F.25.40.cov.45)
MAE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.45 <- MAE(error.infer.clust.cov.100.men.40.50.F.25.40.cov.45)
ARMSE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.45 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men40.50.F.25.40, v2=vector.MAR.cov.45.cl.prop.men40.50.F.25.40)
MRE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.45 <- MRE(error.infer.clust.cov.100.men.40.50.F.25.40.cov.45)
# F.40.50.M.15.25
error.infer.clust.cov.100.women.40.50.M.15.25.cov.45 <- as.numeric(vector.MAR.true.cov.100.prop.women40.50.M.15.25) - as.numeric(vector.MAR.cov.45.cl.prop.women40.50.M.15.25)
RMSE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.45 <- RMSE(error.infer.clust.cov.100.women.40.50.M.15.25.cov.45)
MAE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.45 <- MAE(error.infer.clust.cov.100.women.40.50.M.15.25.cov.45)
ARMSE.error.infer.clust.cov.100.women.cov.45 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women40.50.M.15.25, v2=vector.MAR.cov.45.cl.prop.women40.50.M.15.25)
MRE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.45 <- MRE(error.infer.clust.cov.100.women.40.50.M.15.25.cov.45)
# F.40.50.M.25.40
error.infer.clust.cov.100.women.40.50.M.25.40.cov.45 <- as.numeric(vector.MAR.true.cov.100.prop.women40.50.M.25.40) - as.numeric(vector.MAR.cov.45.cl.prop.women40.50.M.25.40)
RMSE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.45 <- RMSE(error.infer.clust.cov.100.women.40.50.M.25.40.cov.45)
MAE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.45 <- MAE(error.infer.clust.cov.100.women.40.50.M.25.40.cov.45)
ARMSE.error.infer.clust.cov.100.women.cov.45 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women40.50.M.25.40, v2=vector.MAR.cov.45.cl.prop.women40.50.M.25.40)
MRE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.45 <- MRE(error.infer.clust.cov.100.women.40.50.M.25.40.cov.45)
# Cov 50
# 15.25
# M.15.25.F.15.25
error.infer.clust.cov.100.men.15.25.F.15.25.cov.50 <- as.numeric(vector.MAR.true.cov.100.prop.men15.25.F.15.25) - as.numeric(vector.MAR.cov.50.cl.prop.men15.25.F.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.F.15.25.cov.50 <- RMSE(error.infer.clust.cov.100.men.15.25.F.15.25.cov.50)
MAE.error.infer.clust.cov.100.men.15.25cov.35 <- MAE(error.infer.clust.cov.100.men.15.25.F.15.25.cov.50)
ARMSE.error.infer.clust.cov.100.men.15.25cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men15.25.F.15.25, v2=vector.MAR.cov.50.cl.prop.men15.25.F.15.25)
MRE.error.infer.clust.cov.100.men.15.25.F.15.25.cov.50 <- MRE(error.infer.clust.cov.100.men.15.25.F.15.25.cov.50)
# F.15.25.M.15.25
error.infer.clust.cov.100.women.15.25.M.15.25.cov.50 <- as.numeric(vector.MAR.true.cov.100.prop.women15.25.M.15.25) - as.numeric(vector.MAR.cov.50.cl.prop.women15.25.M.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.50 <- RMSE(error.infer.clust.cov.100.women.15.25.M.15.25.cov.50)
MAE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.50 <- MAE(error.infer.clust.cov.100.women.15.25.M.15.25.cov.50)
ARMSE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.50 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women15.25.M.15.25, v2=vector.MAR.cov.50.cl.prop.women15.25.M.15.25)
MRE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.50 <- MRE(error.infer.clust.cov.100.women.15.25.M.15.25.cov.50)
# M.15.25.F.25.40
error.infer.clust.cov.100.men.15.25.F.25.40.cov.50 <- as.numeric(vector.MAR.true.cov.100.prop.men15.25.F.25.40) - as.numeric(vector.MAR.cov.50.cl.prop.men15.25.F.25.40)
RMSE.error.infer.clust.cov.100.men.15.25.F.25.40.cov.50 <- RMSE(error.infer.clust.cov.100.men.15.25.F.25.40.cov.50)
MAE.error.infer.clust.cov.100.men.15.25cov.35 <- MAE(error.infer.clust.cov.100.men.15.25.F.25.40.cov.50)
ARMSE.error.infer.clust.cov.100.men.15.25cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men15.25.F.25.40, v2=vector.MAR.cov.50.cl.prop.men15.25.F.25.40)
MRE.error.infer.clust.cov.100.men.15.25.F.25.40.cov.50 <- MRE(error.infer.clust.cov.100.men.15.25.F.25.40.cov.50)
# M.15.25.F.40.50
error.infer.clust.cov.100.men.15.25.F.40.50.cov.50 <- as.numeric(vector.MAR.true.cov.100.prop.men15.25.F.40.50) - as.numeric(vector.MAR.cov.50.cl.prop.men15.25.F.40.50)
RMSE.error.infer.clust.cov.100.men.15.25.F.40.50.cov.50 <- RMSE(error.infer.clust.cov.100.men.15.25.F.40.50.cov.50)
MAE.error.infer.clust.cov.100.men.15.25cov.35 <- MAE(error.infer.clust.cov.100.men.15.25.F.40.50.cov.50)
ARMSE.error.infer.clust.cov.100.men.15.25cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men15.25.F.40.50, v2=vector.MAR.cov.50.cl.prop.men15.25.F.40.50)
MRE.error.infer.clust.cov.100.men.15.25.F.40.50.cov.50 <- MRE(error.infer.clust.cov.100.men.15.25.F.40.50.cov.50)
# F.15.25.M.25.40
error.infer.clust.cov.100.women.15.25.M.25.40.cov.50 <- as.numeric(vector.MAR.true.cov.100.prop.women15.25.M.25.40) - as.numeric(vector.MAR.cov.50.cl.prop.women15.25.M.25.40)
RMSE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.50 <- RMSE(error.infer.clust.cov.100.women.15.25.M.25.40.cov.50)
MAE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.50 <- MAE(error.infer.clust.cov.100.women.15.25.M.25.40.cov.50)
ARMSE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.50 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women15.25.M.25.40, v2=vector.MAR.cov.50.cl.prop.women15.25.M.25.40)
MRE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.50 <- MRE(error.infer.clust.cov.100.women.15.25.M.25.40.cov.50)
# F.15.25.M.40.50
error.infer.clust.cov.100.women.15.25.M.40.50.cov.50 <- as.numeric(vector.MAR.true.cov.100.prop.women15.25.M.40.50) - as.numeric(vector.MAR.cov.50.cl.prop.women15.25.M.40.50)
RMSE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.50 <- RMSE(error.infer.clust.cov.100.women.15.25.M.40.50.cov.50)
MAE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.50 <- MAE(error.infer.clust.cov.100.women.15.25.M.40.50.cov.50)
ARMSE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.50 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women15.25.M.40.50, v2=vector.MAR.cov.50.cl.prop.women15.25.M.40.50)
MRE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.50 <- MRE(error.infer.clust.cov.100.women.15.25.M.40.50.cov.50)
# 25.40
# M.25.40.F.25.40
error.infer.clust.cov.100.men.25.40.F.25.40.cov.50 <- as.numeric(vector.MAR.true.cov.100.prop.men25.40.F.25.40) - as.numeric(vector.MAR.cov.50.cl.prop.men25.40.F.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.50 <- RMSE(error.infer.clust.cov.100.men.25.40.F.25.40.cov.50)
MAE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.50 <- MAE(error.infer.clust.cov.100.men.25.40.F.25.40.cov.50)
ARMSE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.50 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men25.40.F.25.40, v2=vector.MAR.cov.50.cl.prop.men25.40.F.25.40)
MRE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.50 <- MRE(error.infer.clust.cov.100.men.25.40.F.25.40.cov.50)
# F.25.40.M.25.40
error.infer.clust.cov.100.women.25.40.M.25.40.cov.50 <- as.numeric(vector.MAR.true.cov.100.prop.women25.40.M.25.40) - as.numeric(vector.MAR.cov.50.cl.prop.women25.40.M.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.50 <- RMSE(error.infer.clust.cov.100.women.25.40.M.25.40.cov.50)
MAE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.50 <- MAE(error.infer.clust.cov.100.women.25.40.M.25.40.cov.50)
ARMSE.error.infer.clust.cov.100.women.cov.50 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women25.40.M.25.40, v2=vector.MAR.cov.50.cl.prop.women25.40.M.25.40)
MRE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.50 <- MRE(error.infer.clust.cov.100.women.25.40.M.25.40.cov.50)
# M.25.40.F.15.25
error.infer.clust.cov.100.men.25.40.F.15.25.cov.50 <- as.numeric(vector.MAR.true.cov.100.prop.men25.40.F.15.25) - as.numeric(vector.MAR.cov.50.cl.prop.men25.40.F.15.25)
RMSE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.50 <- RMSE(error.infer.clust.cov.100.men.25.40.F.15.25.cov.50)
MAE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.50 <- MAE(error.infer.clust.cov.100.men.25.40.F.15.25.cov.50)
ARMSE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.50 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men25.40.F.15.25, v2=vector.MAR.cov.50.cl.prop.men25.40.F.15.25)
MRE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.50 <- MRE(error.infer.clust.cov.100.men.25.40.F.15.25.cov.50)
# M.25.40.F.40.50
error.infer.clust.cov.100.men.25.40.F.40.50.cov.50 <- as.numeric(vector.MAR.true.cov.100.prop.men25.40.F.40.50) - as.numeric(vector.MAR.cov.50.cl.prop.men25.40.F.40.50)
RMSE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.50 <- RMSE(error.infer.clust.cov.100.men.25.40.F.40.50.cov.50)
MAE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.50 <- MAE(error.infer.clust.cov.100.men.25.40.F.40.50.cov.50)
ARMSE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.50 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men25.40.F.40.50, v2=vector.MAR.cov.50.cl.prop.men25.40.F.40.50)
MRE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.50 <- MRE(error.infer.clust.cov.100.men.25.40.F.40.50.cov.50)
# F.25.40.M.15.25
error.infer.clust.cov.100.women.25.40.M.15.25.cov.50 <- as.numeric(vector.MAR.true.cov.100.prop.women25.40.M.15.25) - as.numeric(vector.MAR.cov.50.cl.prop.women25.40.M.15.25)
RMSE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.50 <- RMSE(error.infer.clust.cov.100.women.25.40.M.15.25.cov.50)
MAE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.50 <- MAE(error.infer.clust.cov.100.women.25.40.M.15.25.cov.50)
ARMSE.error.infer.clust.cov.100.women.cov.50 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women25.40.M.15.25, v2=vector.MAR.cov.50.cl.prop.women25.40.M.15.25)
MRE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.50 <- MRE(error.infer.clust.cov.100.women.25.40.M.15.25.cov.50)
# F.25.40.M.40.50
error.infer.clust.cov.100.women.25.40.M.40.50.cov.50 <- as.numeric(vector.MAR.true.cov.100.prop.women25.40.M.40.50) - as.numeric(vector.MAR.cov.50.cl.prop.women25.40.M.40.50)
RMSE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.50 <- RMSE(error.infer.clust.cov.100.women.25.40.M.40.50.cov.50)
MAE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.50 <- MAE(error.infer.clust.cov.100.women.25.40.M.40.50.cov.50)
ARMSE.error.infer.clust.cov.100.women.cov.50 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women25.40.M.40.50, v2=vector.MAR.cov.50.cl.prop.women25.40.M.40.50)
MRE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.50 <- MRE(error.infer.clust.cov.100.women.25.40.M.40.50.cov.50)
# 40.50
# M.40.50.F.40.50
error.infer.clust.cov.100.men.40.50.F.40.50.cov.50 <- as.numeric(vector.MAR.true.cov.100.prop.men40.50.F.40.50) - as.numeric(vector.MAR.cov.50.cl.prop.men40.50.F.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.50 <- RMSE(error.infer.clust.cov.100.men.40.50.F.40.50.cov.50)
MAE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.50 <- MAE(error.infer.clust.cov.100.men.40.50.F.40.50.cov.50)
ARMSE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.50 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men40.50.F.40.50, v2=vector.MAR.cov.50.cl.prop.men40.50.F.40.50)
MRE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.50 <- MRE(error.infer.clust.cov.100.men.40.50.F.40.50.cov.50)
# F.40.50.M.40.50
error.infer.clust.cov.100.women.40.50.M.40.50.cov.50 <- as.numeric(vector.MAR.true.cov.100.prop.women40.50.M.40.50) - as.numeric(vector.MAR.cov.50.cl.prop.women40.50.M.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.50 <- RMSE(error.infer.clust.cov.100.women.40.50.M.40.50.cov.50)
MAE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.50 <- MAE(error.infer.clust.cov.100.women.40.50.M.40.50.cov.50)
ARMSE.error.infer.clust.cov.100.women.cov.50 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women40.50.M.40.50, v2=vector.MAR.cov.50.cl.prop.women40.50.M.40.50)
MRE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.50 <- MRE(error.infer.clust.cov.100.women.40.50.M.40.50.cov.50)
# M.40.50.F.15.25
error.infer.clust.cov.100.men.40.50.F.15.25.cov.50 <- as.numeric(vector.MAR.true.cov.100.prop.men40.50.F.15.25) - as.numeric(vector.MAR.cov.50.cl.prop.men40.50.F.15.25)
RMSE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.50 <- RMSE(error.infer.clust.cov.100.men.40.50.F.15.25.cov.50)
MAE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.50 <- MAE(error.infer.clust.cov.100.men.40.50.F.15.25.cov.50)
ARMSE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.50 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men40.50.F.15.25, v2=vector.MAR.cov.50.cl.prop.men40.50.F.15.25)
MRE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.50 <- MRE(error.infer.clust.cov.100.men.40.50.F.15.25.cov.50)
# M.40.50.F.25.40
error.infer.clust.cov.100.men.40.50.F.25.40.cov.50 <- as.numeric(vector.MAR.true.cov.100.prop.men40.50.F.25.40) - as.numeric(vector.MAR.cov.50.cl.prop.men40.50.F.25.40)
RMSE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.50 <- RMSE(error.infer.clust.cov.100.men.40.50.F.25.40.cov.50)
MAE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.50 <- MAE(error.infer.clust.cov.100.men.40.50.F.25.40.cov.50)
ARMSE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.50 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men40.50.F.25.40, v2=vector.MAR.cov.50.cl.prop.men40.50.F.25.40)
MRE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.50 <- MRE(error.infer.clust.cov.100.men.40.50.F.25.40.cov.50)
# F.40.50.M.15.25
error.infer.clust.cov.100.women.40.50.M.15.25.cov.50 <- as.numeric(vector.MAR.true.cov.100.prop.women40.50.M.15.25) - as.numeric(vector.MAR.cov.50.cl.prop.women40.50.M.15.25)
RMSE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.50 <- RMSE(error.infer.clust.cov.100.women.40.50.M.15.25.cov.50)
MAE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.50 <- MAE(error.infer.clust.cov.100.women.40.50.M.15.25.cov.50)
ARMSE.error.infer.clust.cov.100.women.cov.50 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women40.50.M.15.25, v2=vector.MAR.cov.50.cl.prop.women40.50.M.15.25)
MRE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.50 <- MRE(error.infer.clust.cov.100.women.40.50.M.15.25.cov.50)
# F.40.50.M.25.40
error.infer.clust.cov.100.women.40.50.M.25.40.cov.50 <- as.numeric(vector.MAR.true.cov.100.prop.women40.50.M.25.40) - as.numeric(vector.MAR.cov.50.cl.prop.women40.50.M.25.40)
RMSE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.50 <- RMSE(error.infer.clust.cov.100.women.40.50.M.25.40.cov.50)
MAE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.50 <- MAE(error.infer.clust.cov.100.women.40.50.M.25.40.cov.50)
ARMSE.error.infer.clust.cov.100.women.cov.50 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women40.50.M.25.40, v2=vector.MAR.cov.50.cl.prop.women40.50.M.25.40)
MRE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.50 <- MRE(error.infer.clust.cov.100.women.40.50.M.25.40.cov.50)
# Cov 55
# 15.25
# M.15.25.F.15.25
error.infer.clust.cov.100.men.15.25.F.15.25.cov.55 <- as.numeric(vector.MAR.true.cov.100.prop.men15.25.F.15.25) - as.numeric(vector.MAR.cov.55.cl.prop.men15.25.F.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.F.15.25.cov.55 <- RMSE(error.infer.clust.cov.100.men.15.25.F.15.25.cov.55)
MAE.error.infer.clust.cov.100.men.15.25cov.35 <- MAE(error.infer.clust.cov.100.men.15.25.F.15.25.cov.55)
ARMSE.error.infer.clust.cov.100.men.15.25cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men15.25.F.15.25, v2=vector.MAR.cov.55.cl.prop.men15.25.F.15.25)
MRE.error.infer.clust.cov.100.men.15.25.F.15.25.cov.55 <- MRE(error.infer.clust.cov.100.men.15.25.F.15.25.cov.55)
# F.15.25.M.15.25
error.infer.clust.cov.100.women.15.25.M.15.25.cov.55 <- as.numeric(vector.MAR.true.cov.100.prop.women15.25.M.15.25) - as.numeric(vector.MAR.cov.55.cl.prop.women15.25.M.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.55 <- RMSE(error.infer.clust.cov.100.women.15.25.M.15.25.cov.55)
MAE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.55 <- MAE(error.infer.clust.cov.100.women.15.25.M.15.25.cov.55)
ARMSE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.55 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women15.25.M.15.25, v2=vector.MAR.cov.55.cl.prop.women15.25.M.15.25)
MRE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.55 <- MRE(error.infer.clust.cov.100.women.15.25.M.15.25.cov.55)
# M.15.25.F.25.40
error.infer.clust.cov.100.men.15.25.F.25.40.cov.55 <- as.numeric(vector.MAR.true.cov.100.prop.men15.25.F.25.40) - as.numeric(vector.MAR.cov.55.cl.prop.men15.25.F.25.40)
RMSE.error.infer.clust.cov.100.men.15.25.F.25.40.cov.55 <- RMSE(error.infer.clust.cov.100.men.15.25.F.25.40.cov.55)
MAE.error.infer.clust.cov.100.men.15.25cov.35 <- MAE(error.infer.clust.cov.100.men.15.25.F.25.40.cov.55)
ARMSE.error.infer.clust.cov.100.men.15.25cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men15.25.F.25.40, v2=vector.MAR.cov.55.cl.prop.men15.25.F.25.40)
MRE.error.infer.clust.cov.100.men.15.25.F.25.40.cov.55 <- MRE(error.infer.clust.cov.100.men.15.25.F.25.40.cov.55)
# M.15.25.F.40.50
error.infer.clust.cov.100.men.15.25.F.40.50.cov.55 <- as.numeric(vector.MAR.true.cov.100.prop.men15.25.F.40.50) - as.numeric(vector.MAR.cov.55.cl.prop.men15.25.F.40.50)
RMSE.error.infer.clust.cov.100.men.15.25.F.40.50.cov.55 <- RMSE(error.infer.clust.cov.100.men.15.25.F.40.50.cov.55)
MAE.error.infer.clust.cov.100.men.15.25cov.35 <- MAE(error.infer.clust.cov.100.men.15.25.F.40.50.cov.55)
ARMSE.error.infer.clust.cov.100.men.15.25cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men15.25.F.40.50, v2=vector.MAR.cov.55.cl.prop.men15.25.F.40.50)
MRE.error.infer.clust.cov.100.men.15.25.F.40.50.cov.55 <- MRE(error.infer.clust.cov.100.men.15.25.F.40.50.cov.55)
# F.15.25.M.25.40
error.infer.clust.cov.100.women.15.25.M.25.40.cov.55 <- as.numeric(vector.MAR.true.cov.100.prop.women15.25.M.25.40) - as.numeric(vector.MAR.cov.55.cl.prop.women15.25.M.25.40)
RMSE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.55 <- RMSE(error.infer.clust.cov.100.women.15.25.M.25.40.cov.55)
MAE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.55 <- MAE(error.infer.clust.cov.100.women.15.25.M.25.40.cov.55)
ARMSE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.55 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women15.25.M.25.40, v2=vector.MAR.cov.55.cl.prop.women15.25.M.25.40)
MRE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.55 <- MRE(error.infer.clust.cov.100.women.15.25.M.25.40.cov.55)
# F.15.25.M.40.50
error.infer.clust.cov.100.women.15.25.M.40.50.cov.55 <- as.numeric(vector.MAR.true.cov.100.prop.women15.25.M.40.50) - as.numeric(vector.MAR.cov.55.cl.prop.women15.25.M.40.50)
RMSE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.55 <- RMSE(error.infer.clust.cov.100.women.15.25.M.40.50.cov.55)
MAE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.55 <- MAE(error.infer.clust.cov.100.women.15.25.M.40.50.cov.55)
ARMSE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.55 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women15.25.M.40.50, v2=vector.MAR.cov.55.cl.prop.women15.25.M.40.50)
MRE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.55 <- MRE(error.infer.clust.cov.100.women.15.25.M.40.50.cov.55)
# 25.40
# M.25.40.F.25.40
error.infer.clust.cov.100.men.25.40.F.25.40.cov.55 <- as.numeric(vector.MAR.true.cov.100.prop.men25.40.F.25.40) - as.numeric(vector.MAR.cov.55.cl.prop.men25.40.F.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.55 <- RMSE(error.infer.clust.cov.100.men.25.40.F.25.40.cov.55)
MAE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.55 <- MAE(error.infer.clust.cov.100.men.25.40.F.25.40.cov.55)
ARMSE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.55 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men25.40.F.25.40, v2=vector.MAR.cov.55.cl.prop.men25.40.F.25.40)
MRE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.55 <- MRE(error.infer.clust.cov.100.men.25.40.F.25.40.cov.55)
# F.25.40.M.25.40
error.infer.clust.cov.100.women.25.40.M.25.40.cov.55 <- as.numeric(vector.MAR.true.cov.100.prop.women25.40.M.25.40) - as.numeric(vector.MAR.cov.55.cl.prop.women25.40.M.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.55 <- RMSE(error.infer.clust.cov.100.women.25.40.M.25.40.cov.55)
MAE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.55 <- MAE(error.infer.clust.cov.100.women.25.40.M.25.40.cov.55)
ARMSE.error.infer.clust.cov.100.women.cov.55 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women25.40.M.25.40, v2=vector.MAR.cov.55.cl.prop.women25.40.M.25.40)
MRE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.55 <- MRE(error.infer.clust.cov.100.women.25.40.M.25.40.cov.55)
# M.25.40.F.15.25
error.infer.clust.cov.100.men.25.40.F.15.25.cov.55 <- as.numeric(vector.MAR.true.cov.100.prop.men25.40.F.15.25) - as.numeric(vector.MAR.cov.55.cl.prop.men25.40.F.15.25)
RMSE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.55 <- RMSE(error.infer.clust.cov.100.men.25.40.F.15.25.cov.55)
MAE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.55 <- MAE(error.infer.clust.cov.100.men.25.40.F.15.25.cov.55)
ARMSE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.55 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men25.40.F.15.25, v2=vector.MAR.cov.55.cl.prop.men25.40.F.15.25)
MRE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.55 <- MRE(error.infer.clust.cov.100.men.25.40.F.15.25.cov.55)
# M.25.40.F.40.50
error.infer.clust.cov.100.men.25.40.F.40.50.cov.55 <- as.numeric(vector.MAR.true.cov.100.prop.men25.40.F.40.50) - as.numeric(vector.MAR.cov.55.cl.prop.men25.40.F.40.50)
RMSE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.55 <- RMSE(error.infer.clust.cov.100.men.25.40.F.40.50.cov.55)
MAE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.55 <- MAE(error.infer.clust.cov.100.men.25.40.F.40.50.cov.55)
ARMSE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.55 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men25.40.F.40.50, v2=vector.MAR.cov.55.cl.prop.men25.40.F.40.50)
MRE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.55 <- MRE(error.infer.clust.cov.100.men.25.40.F.40.50.cov.55)
# F.25.40.M.15.25
error.infer.clust.cov.100.women.25.40.M.15.25.cov.55 <- as.numeric(vector.MAR.true.cov.100.prop.women25.40.M.15.25) - as.numeric(vector.MAR.cov.55.cl.prop.women25.40.M.15.25)
RMSE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.55 <- RMSE(error.infer.clust.cov.100.women.25.40.M.15.25.cov.55)
MAE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.55 <- MAE(error.infer.clust.cov.100.women.25.40.M.15.25.cov.55)
ARMSE.error.infer.clust.cov.100.women.cov.55 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women25.40.M.15.25, v2=vector.MAR.cov.55.cl.prop.women25.40.M.15.25)
MRE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.55 <- MRE(error.infer.clust.cov.100.women.25.40.M.15.25.cov.55)
# F.25.40.M.40.50
error.infer.clust.cov.100.women.25.40.M.40.50.cov.55 <- as.numeric(vector.MAR.true.cov.100.prop.women25.40.M.40.50) - as.numeric(vector.MAR.cov.55.cl.prop.women25.40.M.40.50)
RMSE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.55 <- RMSE(error.infer.clust.cov.100.women.25.40.M.40.50.cov.55)
MAE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.55 <- MAE(error.infer.clust.cov.100.women.25.40.M.40.50.cov.55)
ARMSE.error.infer.clust.cov.100.women.cov.55 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women25.40.M.40.50, v2=vector.MAR.cov.55.cl.prop.women25.40.M.40.50)
MRE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.55 <- MRE(error.infer.clust.cov.100.women.25.40.M.40.50.cov.55)
# 40.50
# M.40.50.F.40.50
error.infer.clust.cov.100.men.40.50.F.40.50.cov.55 <- as.numeric(vector.MAR.true.cov.100.prop.men40.50.F.40.50) - as.numeric(vector.MAR.cov.55.cl.prop.men40.50.F.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.55 <- RMSE(error.infer.clust.cov.100.men.40.50.F.40.50.cov.55)
MAE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.55 <- MAE(error.infer.clust.cov.100.men.40.50.F.40.50.cov.55)
ARMSE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.55 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men40.50.F.40.50, v2=vector.MAR.cov.55.cl.prop.men40.50.F.40.50)
MRE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.55 <- MRE(error.infer.clust.cov.100.men.40.50.F.40.50.cov.55)
# F.40.50.M.40.50
error.infer.clust.cov.100.women.40.50.M.40.50.cov.55 <- as.numeric(vector.MAR.true.cov.100.prop.women40.50.M.40.50) - as.numeric(vector.MAR.cov.55.cl.prop.women40.50.M.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.55 <- RMSE(error.infer.clust.cov.100.women.40.50.M.40.50.cov.55)
MAE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.55 <- MAE(error.infer.clust.cov.100.women.40.50.M.40.50.cov.55)
ARMSE.error.infer.clust.cov.100.women.cov.55 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women40.50.M.40.50, v2=vector.MAR.cov.55.cl.prop.women40.50.M.40.50)
MRE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.55 <- MRE(error.infer.clust.cov.100.women.40.50.M.40.50.cov.55)
# M.40.50.F.15.25
error.infer.clust.cov.100.men.40.50.F.15.25.cov.55 <- as.numeric(vector.MAR.true.cov.100.prop.men40.50.F.15.25) - as.numeric(vector.MAR.cov.55.cl.prop.men40.50.F.15.25)
RMSE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.55 <- RMSE(error.infer.clust.cov.100.men.40.50.F.15.25.cov.55)
MAE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.55 <- MAE(error.infer.clust.cov.100.men.40.50.F.15.25.cov.55)
ARMSE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.55 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men40.50.F.15.25, v2=vector.MAR.cov.55.cl.prop.men40.50.F.15.25)
MRE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.55 <- MRE(error.infer.clust.cov.100.men.40.50.F.15.25.cov.55)
# M.40.50.F.25.40
error.infer.clust.cov.100.men.40.50.F.25.40.cov.55 <- as.numeric(vector.MAR.true.cov.100.prop.men40.50.F.25.40) - as.numeric(vector.MAR.cov.55.cl.prop.men40.50.F.25.40)
RMSE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.55 <- RMSE(error.infer.clust.cov.100.men.40.50.F.25.40.cov.55)
MAE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.55 <- MAE(error.infer.clust.cov.100.men.40.50.F.25.40.cov.55)
ARMSE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.55 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men40.50.F.25.40, v2=vector.MAR.cov.55.cl.prop.men40.50.F.25.40)
MRE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.55 <- MRE(error.infer.clust.cov.100.men.40.50.F.25.40.cov.55)
# F.40.50.M.15.25
error.infer.clust.cov.100.women.40.50.M.15.25.cov.55 <- as.numeric(vector.MAR.true.cov.100.prop.women40.50.M.15.25) - as.numeric(vector.MAR.cov.55.cl.prop.women40.50.M.15.25)
RMSE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.55 <- RMSE(error.infer.clust.cov.100.women.40.50.M.15.25.cov.55)
MAE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.55 <- MAE(error.infer.clust.cov.100.women.40.50.M.15.25.cov.55)
ARMSE.error.infer.clust.cov.100.women.cov.55 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women40.50.M.15.25, v2=vector.MAR.cov.55.cl.prop.women40.50.M.15.25)
MRE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.55 <- MRE(error.infer.clust.cov.100.women.40.50.M.15.25.cov.55)
# F.40.50.M.25.40
error.infer.clust.cov.100.women.40.50.M.25.40.cov.55 <- as.numeric(vector.MAR.true.cov.100.prop.women40.50.M.25.40) - as.numeric(vector.MAR.cov.55.cl.prop.women40.50.M.25.40)
RMSE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.55 <- RMSE(error.infer.clust.cov.100.women.40.50.M.25.40.cov.55)
MAE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.55 <- MAE(error.infer.clust.cov.100.women.40.50.M.25.40.cov.55)
ARMSE.error.infer.clust.cov.100.women.cov.55 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women40.50.M.25.40, v2=vector.MAR.cov.55.cl.prop.women40.50.M.25.40)
MRE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.55 <- MRE(error.infer.clust.cov.100.women.40.50.M.25.40.cov.55)
# Cov 60
# 15.25
# M.15.25.F.15.25
error.infer.clust.cov.100.men.15.25.F.15.25.cov.60 <- as.numeric(vector.MAR.true.cov.100.prop.men15.25.F.15.25) - as.numeric(vector.MAR.cov.60.cl.prop.men15.25.F.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.F.15.25.cov.60 <- RMSE(error.infer.clust.cov.100.men.15.25.F.15.25.cov.60)
MAE.error.infer.clust.cov.100.men.15.25cov.35 <- MAE(error.infer.clust.cov.100.men.15.25.F.15.25.cov.60)
ARMSE.error.infer.clust.cov.100.men.15.25cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men15.25.F.15.25, v2=vector.MAR.cov.60.cl.prop.men15.25.F.15.25)
MRE.error.infer.clust.cov.100.men.15.25.F.15.25.cov.60 <- MRE(error.infer.clust.cov.100.men.15.25.F.15.25.cov.60)
# F.15.25.M.15.25
error.infer.clust.cov.100.women.15.25.M.15.25.cov.60 <- as.numeric(vector.MAR.true.cov.100.prop.women15.25.M.15.25) - as.numeric(vector.MAR.cov.60.cl.prop.women15.25.M.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.60 <- RMSE(error.infer.clust.cov.100.women.15.25.M.15.25.cov.60)
MAE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.60 <- MAE(error.infer.clust.cov.100.women.15.25.M.15.25.cov.60)
ARMSE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.60 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women15.25.M.15.25, v2=vector.MAR.cov.60.cl.prop.women15.25.M.15.25)
MRE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.60 <- MRE(error.infer.clust.cov.100.women.15.25.M.15.25.cov.60)
# M.15.25.F.25.40
error.infer.clust.cov.100.men.15.25.F.25.40.cov.60 <- as.numeric(vector.MAR.true.cov.100.prop.men15.25.F.25.40) - as.numeric(vector.MAR.cov.60.cl.prop.men15.25.F.25.40)
RMSE.error.infer.clust.cov.100.men.15.25.F.25.40.cov.60 <- RMSE(error.infer.clust.cov.100.men.15.25.F.25.40.cov.60)
MAE.error.infer.clust.cov.100.men.15.25cov.35 <- MAE(error.infer.clust.cov.100.men.15.25.F.25.40.cov.60)
ARMSE.error.infer.clust.cov.100.men.15.25cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men15.25.F.25.40, v2=vector.MAR.cov.60.cl.prop.men15.25.F.25.40)
MRE.error.infer.clust.cov.100.men.15.25.F.25.40.cov.60 <- MRE(error.infer.clust.cov.100.men.15.25.F.25.40.cov.60)
# M.15.25.F.40.50
error.infer.clust.cov.100.men.15.25.F.40.50.cov.60 <- as.numeric(vector.MAR.true.cov.100.prop.men15.25.F.40.50) - as.numeric(vector.MAR.cov.60.cl.prop.men15.25.F.40.50)
RMSE.error.infer.clust.cov.100.men.15.25.F.40.50.cov.60 <- RMSE(error.infer.clust.cov.100.men.15.25.F.40.50.cov.60)
MAE.error.infer.clust.cov.100.men.15.25cov.35 <- MAE(error.infer.clust.cov.100.men.15.25.F.40.50.cov.60)
ARMSE.error.infer.clust.cov.100.men.15.25cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men15.25.F.40.50, v2=vector.MAR.cov.60.cl.prop.men15.25.F.40.50)
MRE.error.infer.clust.cov.100.men.15.25.F.40.50.cov.60 <- MRE(error.infer.clust.cov.100.men.15.25.F.40.50.cov.60)
# F.15.25.M.25.40
error.infer.clust.cov.100.women.15.25.M.25.40.cov.60 <- as.numeric(vector.MAR.true.cov.100.prop.women15.25.M.25.40) - as.numeric(vector.MAR.cov.60.cl.prop.women15.25.M.25.40)
RMSE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.60 <- RMSE(error.infer.clust.cov.100.women.15.25.M.25.40.cov.60)
MAE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.60 <- MAE(error.infer.clust.cov.100.women.15.25.M.25.40.cov.60)
ARMSE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.60 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women15.25.M.25.40, v2=vector.MAR.cov.60.cl.prop.women15.25.M.25.40)
MRE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.60 <- MRE(error.infer.clust.cov.100.women.15.25.M.25.40.cov.60)
# F.15.25.M.40.50
error.infer.clust.cov.100.women.15.25.M.40.50.cov.60 <- as.numeric(vector.MAR.true.cov.100.prop.women15.25.M.40.50) - as.numeric(vector.MAR.cov.60.cl.prop.women15.25.M.40.50)
RMSE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.60 <- RMSE(error.infer.clust.cov.100.women.15.25.M.40.50.cov.60)
MAE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.60 <- MAE(error.infer.clust.cov.100.women.15.25.M.40.50.cov.60)
ARMSE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.60 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women15.25.M.40.50, v2=vector.MAR.cov.60.cl.prop.women15.25.M.40.50)
MRE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.60 <- MRE(error.infer.clust.cov.100.women.15.25.M.40.50.cov.60)
# 25.40
# M.25.40.F.25.40
error.infer.clust.cov.100.men.25.40.F.25.40.cov.60 <- as.numeric(vector.MAR.true.cov.100.prop.men25.40.F.25.40) - as.numeric(vector.MAR.cov.60.cl.prop.men25.40.F.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.60 <- RMSE(error.infer.clust.cov.100.men.25.40.F.25.40.cov.60)
MAE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.60 <- MAE(error.infer.clust.cov.100.men.25.40.F.25.40.cov.60)
ARMSE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.60 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men25.40.F.25.40, v2=vector.MAR.cov.60.cl.prop.men25.40.F.25.40)
MRE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.60 <- MRE(error.infer.clust.cov.100.men.25.40.F.25.40.cov.60)
# F.25.40.M.25.40
error.infer.clust.cov.100.women.25.40.M.25.40.cov.60 <- as.numeric(vector.MAR.true.cov.100.prop.women25.40.M.25.40) - as.numeric(vector.MAR.cov.60.cl.prop.women25.40.M.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.60 <- RMSE(error.infer.clust.cov.100.women.25.40.M.25.40.cov.60)
MAE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.60 <- MAE(error.infer.clust.cov.100.women.25.40.M.25.40.cov.60)
ARMSE.error.infer.clust.cov.100.women.cov.60 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women25.40.M.25.40, v2=vector.MAR.cov.60.cl.prop.women25.40.M.25.40)
MRE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.60 <- MRE(error.infer.clust.cov.100.women.25.40.M.25.40.cov.60)
# M.25.40.F.15.25
error.infer.clust.cov.100.men.25.40.F.15.25.cov.60 <- as.numeric(vector.MAR.true.cov.100.prop.men25.40.F.15.25) - as.numeric(vector.MAR.cov.60.cl.prop.men25.40.F.15.25)
RMSE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.60 <- RMSE(error.infer.clust.cov.100.men.25.40.F.15.25.cov.60)
MAE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.60 <- MAE(error.infer.clust.cov.100.men.25.40.F.15.25.cov.60)
ARMSE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.60 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men25.40.F.15.25, v2=vector.MAR.cov.60.cl.prop.men25.40.F.15.25)
MRE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.60 <- MRE(error.infer.clust.cov.100.men.25.40.F.15.25.cov.60)
# M.25.40.F.40.50
error.infer.clust.cov.100.men.25.40.F.40.50.cov.60 <- as.numeric(vector.MAR.true.cov.100.prop.men25.40.F.40.50) - as.numeric(vector.MAR.cov.60.cl.prop.men25.40.F.40.50)
RMSE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.60 <- RMSE(error.infer.clust.cov.100.men.25.40.F.40.50.cov.60)
MAE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.60 <- MAE(error.infer.clust.cov.100.men.25.40.F.40.50.cov.60)
ARMSE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.60 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men25.40.F.40.50, v2=vector.MAR.cov.60.cl.prop.men25.40.F.40.50)
MRE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.60 <- MRE(error.infer.clust.cov.100.men.25.40.F.40.50.cov.60)
# F.25.40.M.15.25
error.infer.clust.cov.100.women.25.40.M.15.25.cov.60 <- as.numeric(vector.MAR.true.cov.100.prop.women25.40.M.15.25) - as.numeric(vector.MAR.cov.60.cl.prop.women25.40.M.15.25)
RMSE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.60 <- RMSE(error.infer.clust.cov.100.women.25.40.M.15.25.cov.60)
MAE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.60 <- MAE(error.infer.clust.cov.100.women.25.40.M.15.25.cov.60)
ARMSE.error.infer.clust.cov.100.women.cov.60 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women25.40.M.15.25, v2=vector.MAR.cov.60.cl.prop.women25.40.M.15.25)
MRE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.60 <- MRE(error.infer.clust.cov.100.women.25.40.M.15.25.cov.60)
# F.25.40.M.40.50
error.infer.clust.cov.100.women.25.40.M.40.50.cov.60 <- as.numeric(vector.MAR.true.cov.100.prop.women25.40.M.40.50) - as.numeric(vector.MAR.cov.60.cl.prop.women25.40.M.40.50)
RMSE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.60 <- RMSE(error.infer.clust.cov.100.women.25.40.M.40.50.cov.60)
MAE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.60 <- MAE(error.infer.clust.cov.100.women.25.40.M.40.50.cov.60)
ARMSE.error.infer.clust.cov.100.women.cov.60 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women25.40.M.40.50, v2=vector.MAR.cov.60.cl.prop.women25.40.M.40.50)
MRE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.60 <- MRE(error.infer.clust.cov.100.women.25.40.M.40.50.cov.60)
# 40.50
# M.40.50.F.40.50
error.infer.clust.cov.100.men.40.50.F.40.50.cov.60 <- as.numeric(vector.MAR.true.cov.100.prop.men40.50.F.40.50) - as.numeric(vector.MAR.cov.60.cl.prop.men40.50.F.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.60 <- RMSE(error.infer.clust.cov.100.men.40.50.F.40.50.cov.60)
MAE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.60 <- MAE(error.infer.clust.cov.100.men.40.50.F.40.50.cov.60)
ARMSE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.60 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men40.50.F.40.50, v2=vector.MAR.cov.60.cl.prop.men40.50.F.40.50)
MRE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.60 <- MRE(error.infer.clust.cov.100.men.40.50.F.40.50.cov.60)
# F.40.50.M.40.50
error.infer.clust.cov.100.women.40.50.M.40.50.cov.60 <- as.numeric(vector.MAR.true.cov.100.prop.women40.50.M.40.50) - as.numeric(vector.MAR.cov.60.cl.prop.women40.50.M.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.60 <- RMSE(error.infer.clust.cov.100.women.40.50.M.40.50.cov.60)
MAE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.60 <- MAE(error.infer.clust.cov.100.women.40.50.M.40.50.cov.60)
ARMSE.error.infer.clust.cov.100.women.cov.60 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women40.50.M.40.50, v2=vector.MAR.cov.60.cl.prop.women40.50.M.40.50)
MRE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.60 <- MRE(error.infer.clust.cov.100.women.40.50.M.40.50.cov.60)
# M.40.50.F.15.25
error.infer.clust.cov.100.men.40.50.F.15.25.cov.60 <- as.numeric(vector.MAR.true.cov.100.prop.men40.50.F.15.25) - as.numeric(vector.MAR.cov.60.cl.prop.men40.50.F.15.25)
RMSE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.60 <- RMSE(error.infer.clust.cov.100.men.40.50.F.15.25.cov.60)
MAE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.60 <- MAE(error.infer.clust.cov.100.men.40.50.F.15.25.cov.60)
ARMSE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.60 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men40.50.F.15.25, v2=vector.MAR.cov.60.cl.prop.men40.50.F.15.25)
MRE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.60 <- MRE(error.infer.clust.cov.100.men.40.50.F.15.25.cov.60)
# M.40.50.F.25.40
error.infer.clust.cov.100.men.40.50.F.25.40.cov.60 <- as.numeric(vector.MAR.true.cov.100.prop.men40.50.F.25.40) - as.numeric(vector.MAR.cov.60.cl.prop.men40.50.F.25.40)
RMSE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.60 <- RMSE(error.infer.clust.cov.100.men.40.50.F.25.40.cov.60)
MAE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.60 <- MAE(error.infer.clust.cov.100.men.40.50.F.25.40.cov.60)
ARMSE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.60 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men40.50.F.25.40, v2=vector.MAR.cov.60.cl.prop.men40.50.F.25.40)
MRE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.60 <- MRE(error.infer.clust.cov.100.men.40.50.F.25.40.cov.60)
# F.40.50.M.15.25
error.infer.clust.cov.100.women.40.50.M.15.25.cov.60 <- as.numeric(vector.MAR.true.cov.100.prop.women40.50.M.15.25) - as.numeric(vector.MAR.cov.60.cl.prop.women40.50.M.15.25)
RMSE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.60 <- RMSE(error.infer.clust.cov.100.women.40.50.M.15.25.cov.60)
MAE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.60 <- MAE(error.infer.clust.cov.100.women.40.50.M.15.25.cov.60)
ARMSE.error.infer.clust.cov.100.women.cov.60 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women40.50.M.15.25, v2=vector.MAR.cov.60.cl.prop.women40.50.M.15.25)
MRE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.60 <- MRE(error.infer.clust.cov.100.women.40.50.M.15.25.cov.60)
# F.40.50.M.25.40
error.infer.clust.cov.100.women.40.50.M.25.40.cov.60 <- as.numeric(vector.MAR.true.cov.100.prop.women40.50.M.25.40) - as.numeric(vector.MAR.cov.60.cl.prop.women40.50.M.25.40)
RMSE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.60 <- RMSE(error.infer.clust.cov.100.women.40.50.M.25.40.cov.60)
MAE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.60 <- MAE(error.infer.clust.cov.100.women.40.50.M.25.40.cov.60)
ARMSE.error.infer.clust.cov.100.women.cov.60 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women40.50.M.25.40, v2=vector.MAR.cov.60.cl.prop.women40.50.M.25.40)
MRE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.60 <- MRE(error.infer.clust.cov.100.women.40.50.M.25.40.cov.60)
# Cov 65
# 15.25
# M.15.25.F.15.25
error.infer.clust.cov.100.men.15.25.F.15.25.cov.65 <- as.numeric(vector.MAR.true.cov.100.prop.men15.25.F.15.25) - as.numeric(vector.MAR.cov.65.cl.prop.men15.25.F.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.F.15.25.cov.65 <- RMSE(error.infer.clust.cov.100.men.15.25.F.15.25.cov.65)
MAE.error.infer.clust.cov.100.men.15.25cov.35 <- MAE(error.infer.clust.cov.100.men.15.25.F.15.25.cov.65)
ARMSE.error.infer.clust.cov.100.men.15.25cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men15.25.F.15.25, v2=vector.MAR.cov.65.cl.prop.men15.25.F.15.25)
MRE.error.infer.clust.cov.100.men.15.25.F.15.25.cov.65 <- MRE(error.infer.clust.cov.100.men.15.25.F.15.25.cov.65)
# F.15.25.M.15.25
error.infer.clust.cov.100.women.15.25.M.15.25.cov.65 <- as.numeric(vector.MAR.true.cov.100.prop.women15.25.M.15.25) - as.numeric(vector.MAR.cov.65.cl.prop.women15.25.M.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.65 <- RMSE(error.infer.clust.cov.100.women.15.25.M.15.25.cov.65)
MAE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.65 <- MAE(error.infer.clust.cov.100.women.15.25.M.15.25.cov.65)
ARMSE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.65 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women15.25.M.15.25, v2=vector.MAR.cov.65.cl.prop.women15.25.M.15.25)
MRE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.65 <- MRE(error.infer.clust.cov.100.women.15.25.M.15.25.cov.65)
# M.15.25.F.25.40
error.infer.clust.cov.100.men.15.25.F.25.40.cov.65 <- as.numeric(vector.MAR.true.cov.100.prop.men15.25.F.25.40) - as.numeric(vector.MAR.cov.65.cl.prop.men15.25.F.25.40)
RMSE.error.infer.clust.cov.100.men.15.25.F.25.40.cov.65 <- RMSE(error.infer.clust.cov.100.men.15.25.F.25.40.cov.65)
MAE.error.infer.clust.cov.100.men.15.25cov.35 <- MAE(error.infer.clust.cov.100.men.15.25.F.25.40.cov.65)
ARMSE.error.infer.clust.cov.100.men.15.25cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men15.25.F.25.40, v2=vector.MAR.cov.65.cl.prop.men15.25.F.25.40)
MRE.error.infer.clust.cov.100.men.15.25.F.25.40.cov.65 <- MRE(error.infer.clust.cov.100.men.15.25.F.25.40.cov.65)
# M.15.25.F.40.50
error.infer.clust.cov.100.men.15.25.F.40.50.cov.65 <- as.numeric(vector.MAR.true.cov.100.prop.men15.25.F.40.50) - as.numeric(vector.MAR.cov.65.cl.prop.men15.25.F.40.50)
RMSE.error.infer.clust.cov.100.men.15.25.F.40.50.cov.65 <- RMSE(error.infer.clust.cov.100.men.15.25.F.40.50.cov.65)
MAE.error.infer.clust.cov.100.men.15.25cov.35 <- MAE(error.infer.clust.cov.100.men.15.25.F.40.50.cov.65)
ARMSE.error.infer.clust.cov.100.men.15.25cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men15.25.F.40.50, v2=vector.MAR.cov.65.cl.prop.men15.25.F.40.50)
MRE.error.infer.clust.cov.100.men.15.25.F.40.50.cov.65 <- MRE(error.infer.clust.cov.100.men.15.25.F.40.50.cov.65)
# F.15.25.M.25.40
error.infer.clust.cov.100.women.15.25.M.25.40.cov.65 <- as.numeric(vector.MAR.true.cov.100.prop.women15.25.M.25.40) - as.numeric(vector.MAR.cov.65.cl.prop.women15.25.M.25.40)
RMSE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.65 <- RMSE(error.infer.clust.cov.100.women.15.25.M.25.40.cov.65)
MAE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.65 <- MAE(error.infer.clust.cov.100.women.15.25.M.25.40.cov.65)
ARMSE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.65 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women15.25.M.25.40, v2=vector.MAR.cov.65.cl.prop.women15.25.M.25.40)
MRE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.65 <- MRE(error.infer.clust.cov.100.women.15.25.M.25.40.cov.65)
# F.15.25.M.40.50
error.infer.clust.cov.100.women.15.25.M.40.50.cov.65 <- as.numeric(vector.MAR.true.cov.100.prop.women15.25.M.40.50) - as.numeric(vector.MAR.cov.65.cl.prop.women15.25.M.40.50)
RMSE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.65 <- RMSE(error.infer.clust.cov.100.women.15.25.M.40.50.cov.65)
MAE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.65 <- MAE(error.infer.clust.cov.100.women.15.25.M.40.50.cov.65)
ARMSE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.65 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women15.25.M.40.50, v2=vector.MAR.cov.65.cl.prop.women15.25.M.40.50)
MRE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.65 <- MRE(error.infer.clust.cov.100.women.15.25.M.40.50.cov.65)
# 25.40
# M.25.40.F.25.40
error.infer.clust.cov.100.men.25.40.F.25.40.cov.65 <- as.numeric(vector.MAR.true.cov.100.prop.men25.40.F.25.40) - as.numeric(vector.MAR.cov.65.cl.prop.men25.40.F.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.65 <- RMSE(error.infer.clust.cov.100.men.25.40.F.25.40.cov.65)
MAE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.65 <- MAE(error.infer.clust.cov.100.men.25.40.F.25.40.cov.65)
ARMSE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.65 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men25.40.F.25.40, v2=vector.MAR.cov.65.cl.prop.men25.40.F.25.40)
MRE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.65 <- MRE(error.infer.clust.cov.100.men.25.40.F.25.40.cov.65)
# F.25.40.M.25.40
error.infer.clust.cov.100.women.25.40.M.25.40.cov.65 <- as.numeric(vector.MAR.true.cov.100.prop.women25.40.M.25.40) - as.numeric(vector.MAR.cov.65.cl.prop.women25.40.M.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.65 <- RMSE(error.infer.clust.cov.100.women.25.40.M.25.40.cov.65)
MAE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.65 <- MAE(error.infer.clust.cov.100.women.25.40.M.25.40.cov.65)
ARMSE.error.infer.clust.cov.100.women.cov.65 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women25.40.M.25.40, v2=vector.MAR.cov.65.cl.prop.women25.40.M.25.40)
MRE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.65 <- MRE(error.infer.clust.cov.100.women.25.40.M.25.40.cov.65)
# M.25.40.F.15.25
error.infer.clust.cov.100.men.25.40.F.15.25.cov.65 <- as.numeric(vector.MAR.true.cov.100.prop.men25.40.F.15.25) - as.numeric(vector.MAR.cov.65.cl.prop.men25.40.F.15.25)
RMSE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.65 <- RMSE(error.infer.clust.cov.100.men.25.40.F.15.25.cov.65)
MAE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.65 <- MAE(error.infer.clust.cov.100.men.25.40.F.15.25.cov.65)
ARMSE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.65 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men25.40.F.15.25, v2=vector.MAR.cov.65.cl.prop.men25.40.F.15.25)
MRE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.65 <- MRE(error.infer.clust.cov.100.men.25.40.F.15.25.cov.65)
# M.25.40.F.40.50
error.infer.clust.cov.100.men.25.40.F.40.50.cov.65 <- as.numeric(vector.MAR.true.cov.100.prop.men25.40.F.40.50) - as.numeric(vector.MAR.cov.65.cl.prop.men25.40.F.40.50)
RMSE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.65 <- RMSE(error.infer.clust.cov.100.men.25.40.F.40.50.cov.65)
MAE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.65 <- MAE(error.infer.clust.cov.100.men.25.40.F.40.50.cov.65)
ARMSE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.65 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men25.40.F.40.50, v2=vector.MAR.cov.65.cl.prop.men25.40.F.40.50)
MRE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.65 <- MRE(error.infer.clust.cov.100.men.25.40.F.40.50.cov.65)
# F.25.40.M.15.25
error.infer.clust.cov.100.women.25.40.M.15.25.cov.65 <- as.numeric(vector.MAR.true.cov.100.prop.women25.40.M.15.25) - as.numeric(vector.MAR.cov.65.cl.prop.women25.40.M.15.25)
RMSE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.65 <- RMSE(error.infer.clust.cov.100.women.25.40.M.15.25.cov.65)
MAE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.65 <- MAE(error.infer.clust.cov.100.women.25.40.M.15.25.cov.65)
ARMSE.error.infer.clust.cov.100.women.cov.65 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women25.40.M.15.25, v2=vector.MAR.cov.65.cl.prop.women25.40.M.15.25)
MRE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.65 <- MRE(error.infer.clust.cov.100.women.25.40.M.15.25.cov.65)
# F.25.40.M.40.50
error.infer.clust.cov.100.women.25.40.M.40.50.cov.65 <- as.numeric(vector.MAR.true.cov.100.prop.women25.40.M.40.50) - as.numeric(vector.MAR.cov.65.cl.prop.women25.40.M.40.50)
RMSE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.65 <- RMSE(error.infer.clust.cov.100.women.25.40.M.40.50.cov.65)
MAE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.65 <- MAE(error.infer.clust.cov.100.women.25.40.M.40.50.cov.65)
ARMSE.error.infer.clust.cov.100.women.cov.65 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women25.40.M.40.50, v2=vector.MAR.cov.65.cl.prop.women25.40.M.40.50)
MRE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.65 <- MRE(error.infer.clust.cov.100.women.25.40.M.40.50.cov.65)
# 40.50
# M.40.50.F.40.50
error.infer.clust.cov.100.men.40.50.F.40.50.cov.65 <- as.numeric(vector.MAR.true.cov.100.prop.men40.50.F.40.50) - as.numeric(vector.MAR.cov.65.cl.prop.men40.50.F.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.65 <- RMSE(error.infer.clust.cov.100.men.40.50.F.40.50.cov.65)
MAE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.65 <- MAE(error.infer.clust.cov.100.men.40.50.F.40.50.cov.65)
ARMSE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.65 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men40.50.F.40.50, v2=vector.MAR.cov.65.cl.prop.men40.50.F.40.50)
MRE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.65 <- MRE(error.infer.clust.cov.100.men.40.50.F.40.50.cov.65)
# F.40.50.M.40.50
error.infer.clust.cov.100.women.40.50.M.40.50.cov.65 <- as.numeric(vector.MAR.true.cov.100.prop.women40.50.M.40.50) - as.numeric(vector.MAR.cov.65.cl.prop.women40.50.M.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.65 <- RMSE(error.infer.clust.cov.100.women.40.50.M.40.50.cov.65)
MAE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.65 <- MAE(error.infer.clust.cov.100.women.40.50.M.40.50.cov.65)
ARMSE.error.infer.clust.cov.100.women.cov.65 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women40.50.M.40.50, v2=vector.MAR.cov.65.cl.prop.women40.50.M.40.50)
MRE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.65 <- MRE(error.infer.clust.cov.100.women.40.50.M.40.50.cov.65)
# M.40.50.F.15.25
error.infer.clust.cov.100.men.40.50.F.15.25.cov.65 <- as.numeric(vector.MAR.true.cov.100.prop.men40.50.F.15.25) - as.numeric(vector.MAR.cov.65.cl.prop.men40.50.F.15.25)
RMSE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.65 <- RMSE(error.infer.clust.cov.100.men.40.50.F.15.25.cov.65)
MAE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.65 <- MAE(error.infer.clust.cov.100.men.40.50.F.15.25.cov.65)
ARMSE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.65 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men40.50.F.15.25, v2=vector.MAR.cov.65.cl.prop.men40.50.F.15.25)
MRE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.65 <- MRE(error.infer.clust.cov.100.men.40.50.F.15.25.cov.65)
# M.40.50.F.25.40
error.infer.clust.cov.100.men.40.50.F.25.40.cov.65 <- as.numeric(vector.MAR.true.cov.100.prop.men40.50.F.25.40) - as.numeric(vector.MAR.cov.65.cl.prop.men40.50.F.25.40)
RMSE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.65 <- RMSE(error.infer.clust.cov.100.men.40.50.F.25.40.cov.65)
MAE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.65 <- MAE(error.infer.clust.cov.100.men.40.50.F.25.40.cov.65)
ARMSE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.65 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men40.50.F.25.40, v2=vector.MAR.cov.65.cl.prop.men40.50.F.25.40)
MRE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.65 <- MRE(error.infer.clust.cov.100.men.40.50.F.25.40.cov.65)
# F.40.50.M.15.25
error.infer.clust.cov.100.women.40.50.M.15.25.cov.65 <- as.numeric(vector.MAR.true.cov.100.prop.women40.50.M.15.25) - as.numeric(vector.MAR.cov.65.cl.prop.women40.50.M.15.25)
RMSE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.65 <- RMSE(error.infer.clust.cov.100.women.40.50.M.15.25.cov.65)
MAE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.65 <- MAE(error.infer.clust.cov.100.women.40.50.M.15.25.cov.65)
ARMSE.error.infer.clust.cov.100.women.cov.65 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women40.50.M.15.25, v2=vector.MAR.cov.65.cl.prop.women40.50.M.15.25)
MRE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.65 <- MRE(error.infer.clust.cov.100.women.40.50.M.15.25.cov.65)
# F.40.50.M.25.40
error.infer.clust.cov.100.women.40.50.M.25.40.cov.65 <- as.numeric(vector.MAR.true.cov.100.prop.women40.50.M.25.40) - as.numeric(vector.MAR.cov.65.cl.prop.women40.50.M.25.40)
RMSE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.65 <- RMSE(error.infer.clust.cov.100.women.40.50.M.25.40.cov.65)
MAE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.65 <- MAE(error.infer.clust.cov.100.women.40.50.M.25.40.cov.65)
ARMSE.error.infer.clust.cov.100.women.cov.65 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women40.50.M.25.40, v2=vector.MAR.cov.65.cl.prop.women40.50.M.25.40)
MRE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.65 <- MRE(error.infer.clust.cov.100.women.40.50.M.25.40.cov.65)
# Cov 70
# 15.25
# M.15.25.F.15.25
error.infer.clust.cov.100.men.15.25.F.15.25.cov.70 <- as.numeric(vector.MAR.true.cov.100.prop.men15.25.F.15.25) - as.numeric(vector.MAR.cov.70.cl.prop.men15.25.F.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.F.15.25.cov.70 <- RMSE(error.infer.clust.cov.100.men.15.25.F.15.25.cov.70)
MAE.error.infer.clust.cov.100.men.15.25cov.35 <- MAE(error.infer.clust.cov.100.men.15.25.F.15.25.cov.70)
ARMSE.error.infer.clust.cov.100.men.15.25cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men15.25.F.15.25, v2=vector.MAR.cov.70.cl.prop.men15.25.F.15.25)
MRE.error.infer.clust.cov.100.men.15.25.F.15.25.cov.70 <- MRE(error.infer.clust.cov.100.men.15.25.F.15.25.cov.70)
# F.15.25.M.15.25
error.infer.clust.cov.100.women.15.25.M.15.25.cov.70 <- as.numeric(vector.MAR.true.cov.100.prop.women15.25.M.15.25) - as.numeric(vector.MAR.cov.70.cl.prop.women15.25.M.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.70 <- RMSE(error.infer.clust.cov.100.women.15.25.M.15.25.cov.70)
MAE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.70 <- MAE(error.infer.clust.cov.100.women.15.25.M.15.25.cov.70)
ARMSE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.70 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women15.25.M.15.25, v2=vector.MAR.cov.70.cl.prop.women15.25.M.15.25)
MRE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.70 <- MRE(error.infer.clust.cov.100.women.15.25.M.15.25.cov.70)
# M.15.25.F.25.40
error.infer.clust.cov.100.men.15.25.F.25.40.cov.70 <- as.numeric(vector.MAR.true.cov.100.prop.men15.25.F.25.40) - as.numeric(vector.MAR.cov.70.cl.prop.men15.25.F.25.40)
RMSE.error.infer.clust.cov.100.men.15.25.F.25.40.cov.70 <- RMSE(error.infer.clust.cov.100.men.15.25.F.25.40.cov.70)
MAE.error.infer.clust.cov.100.men.15.25cov.35 <- MAE(error.infer.clust.cov.100.men.15.25.F.25.40.cov.70)
ARMSE.error.infer.clust.cov.100.men.15.25cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men15.25.F.25.40, v2=vector.MAR.cov.70.cl.prop.men15.25.F.25.40)
MRE.error.infer.clust.cov.100.men.15.25.F.25.40.cov.70 <- MRE(error.infer.clust.cov.100.men.15.25.F.25.40.cov.70)
# M.15.25.F.40.50
error.infer.clust.cov.100.men.15.25.F.40.50.cov.70 <- as.numeric(vector.MAR.true.cov.100.prop.men15.25.F.40.50) - as.numeric(vector.MAR.cov.70.cl.prop.men15.25.F.40.50)
RMSE.error.infer.clust.cov.100.men.15.25.F.40.50.cov.70 <- RMSE(error.infer.clust.cov.100.men.15.25.F.40.50.cov.70)
MAE.error.infer.clust.cov.100.men.15.25cov.35 <- MAE(error.infer.clust.cov.100.men.15.25.F.40.50.cov.70)
ARMSE.error.infer.clust.cov.100.men.15.25cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men15.25.F.40.50, v2=vector.MAR.cov.70.cl.prop.men15.25.F.40.50)
MRE.error.infer.clust.cov.100.men.15.25.F.40.50.cov.70 <- MRE(error.infer.clust.cov.100.men.15.25.F.40.50.cov.70)
# F.15.25.M.25.40
error.infer.clust.cov.100.women.15.25.M.25.40.cov.70 <- as.numeric(vector.MAR.true.cov.100.prop.women15.25.M.25.40) - as.numeric(vector.MAR.cov.70.cl.prop.women15.25.M.25.40)
RMSE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.70 <- RMSE(error.infer.clust.cov.100.women.15.25.M.25.40.cov.70)
MAE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.70 <- MAE(error.infer.clust.cov.100.women.15.25.M.25.40.cov.70)
ARMSE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.70 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women15.25.M.25.40, v2=vector.MAR.cov.70.cl.prop.women15.25.M.25.40)
MRE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.70 <- MRE(error.infer.clust.cov.100.women.15.25.M.25.40.cov.70)
# F.15.25.M.40.50
error.infer.clust.cov.100.women.15.25.M.40.50.cov.70 <- as.numeric(vector.MAR.true.cov.100.prop.women15.25.M.40.50) - as.numeric(vector.MAR.cov.70.cl.prop.women15.25.M.40.50)
RMSE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.70 <- RMSE(error.infer.clust.cov.100.women.15.25.M.40.50.cov.70)
MAE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.70 <- MAE(error.infer.clust.cov.100.women.15.25.M.40.50.cov.70)
ARMSE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.70 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women15.25.M.40.50, v2=vector.MAR.cov.70.cl.prop.women15.25.M.40.50)
MRE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.70 <- MRE(error.infer.clust.cov.100.women.15.25.M.40.50.cov.70)
# 25.40
# M.25.40.F.25.40
error.infer.clust.cov.100.men.25.40.F.25.40.cov.70 <- as.numeric(vector.MAR.true.cov.100.prop.men25.40.F.25.40) - as.numeric(vector.MAR.cov.70.cl.prop.men25.40.F.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.70 <- RMSE(error.infer.clust.cov.100.men.25.40.F.25.40.cov.70)
MAE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.70 <- MAE(error.infer.clust.cov.100.men.25.40.F.25.40.cov.70)
ARMSE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.70 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men25.40.F.25.40, v2=vector.MAR.cov.70.cl.prop.men25.40.F.25.40)
MRE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.70 <- MRE(error.infer.clust.cov.100.men.25.40.F.25.40.cov.70)
# F.25.40.M.25.40
error.infer.clust.cov.100.women.25.40.M.25.40.cov.70 <- as.numeric(vector.MAR.true.cov.100.prop.women25.40.M.25.40) - as.numeric(vector.MAR.cov.70.cl.prop.women25.40.M.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.70 <- RMSE(error.infer.clust.cov.100.women.25.40.M.25.40.cov.70)
MAE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.70 <- MAE(error.infer.clust.cov.100.women.25.40.M.25.40.cov.70)
ARMSE.error.infer.clust.cov.100.women.cov.70 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women25.40.M.25.40, v2=vector.MAR.cov.70.cl.prop.women25.40.M.25.40)
MRE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.70 <- MRE(error.infer.clust.cov.100.women.25.40.M.25.40.cov.70)
# M.25.40.F.15.25
error.infer.clust.cov.100.men.25.40.F.15.25.cov.70 <- as.numeric(vector.MAR.true.cov.100.prop.men25.40.F.15.25) - as.numeric(vector.MAR.cov.70.cl.prop.men25.40.F.15.25)
RMSE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.70 <- RMSE(error.infer.clust.cov.100.men.25.40.F.15.25.cov.70)
MAE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.70 <- MAE(error.infer.clust.cov.100.men.25.40.F.15.25.cov.70)
ARMSE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.70 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men25.40.F.15.25, v2=vector.MAR.cov.70.cl.prop.men25.40.F.15.25)
MRE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.70 <- MRE(error.infer.clust.cov.100.men.25.40.F.15.25.cov.70)
# M.25.40.F.40.50
error.infer.clust.cov.100.men.25.40.F.40.50.cov.70 <- as.numeric(vector.MAR.true.cov.100.prop.men25.40.F.40.50) - as.numeric(vector.MAR.cov.70.cl.prop.men25.40.F.40.50)
RMSE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.70 <- RMSE(error.infer.clust.cov.100.men.25.40.F.40.50.cov.70)
MAE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.70 <- MAE(error.infer.clust.cov.100.men.25.40.F.40.50.cov.70)
ARMSE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.70 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men25.40.F.40.50, v2=vector.MAR.cov.70.cl.prop.men25.40.F.40.50)
MRE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.70 <- MRE(error.infer.clust.cov.100.men.25.40.F.40.50.cov.70)
# F.25.40.M.15.25
error.infer.clust.cov.100.women.25.40.M.15.25.cov.70 <- as.numeric(vector.MAR.true.cov.100.prop.women25.40.M.15.25) - as.numeric(vector.MAR.cov.70.cl.prop.women25.40.M.15.25)
RMSE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.70 <- RMSE(error.infer.clust.cov.100.women.25.40.M.15.25.cov.70)
MAE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.70 <- MAE(error.infer.clust.cov.100.women.25.40.M.15.25.cov.70)
ARMSE.error.infer.clust.cov.100.women.cov.70 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women25.40.M.15.25, v2=vector.MAR.cov.70.cl.prop.women25.40.M.15.25)
MRE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.70 <- MRE(error.infer.clust.cov.100.women.25.40.M.15.25.cov.70)
# F.25.40.M.40.50
error.infer.clust.cov.100.women.25.40.M.40.50.cov.70 <- as.numeric(vector.MAR.true.cov.100.prop.women25.40.M.40.50) - as.numeric(vector.MAR.cov.70.cl.prop.women25.40.M.40.50)
RMSE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.70 <- RMSE(error.infer.clust.cov.100.women.25.40.M.40.50.cov.70)
MAE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.70 <- MAE(error.infer.clust.cov.100.women.25.40.M.40.50.cov.70)
ARMSE.error.infer.clust.cov.100.women.cov.70 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women25.40.M.40.50, v2=vector.MAR.cov.70.cl.prop.women25.40.M.40.50)
MRE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.70 <- MRE(error.infer.clust.cov.100.women.25.40.M.40.50.cov.70)
# 40.50
# M.40.50.F.40.50
error.infer.clust.cov.100.men.40.50.F.40.50.cov.70 <- as.numeric(vector.MAR.true.cov.100.prop.men40.50.F.40.50) - as.numeric(vector.MAR.cov.70.cl.prop.men40.50.F.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.70 <- RMSE(error.infer.clust.cov.100.men.40.50.F.40.50.cov.70)
MAE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.70 <- MAE(error.infer.clust.cov.100.men.40.50.F.40.50.cov.70)
ARMSE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.70 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men40.50.F.40.50, v2=vector.MAR.cov.70.cl.prop.men40.50.F.40.50)
MRE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.70 <- MRE(error.infer.clust.cov.100.men.40.50.F.40.50.cov.70)
# F.40.50.M.40.50
error.infer.clust.cov.100.women.40.50.M.40.50.cov.70 <- as.numeric(vector.MAR.true.cov.100.prop.women40.50.M.40.50) - as.numeric(vector.MAR.cov.70.cl.prop.women40.50.M.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.70 <- RMSE(error.infer.clust.cov.100.women.40.50.M.40.50.cov.70)
MAE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.70 <- MAE(error.infer.clust.cov.100.women.40.50.M.40.50.cov.70)
ARMSE.error.infer.clust.cov.100.women.cov.70 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women40.50.M.40.50, v2=vector.MAR.cov.70.cl.prop.women40.50.M.40.50)
MRE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.70 <- MRE(error.infer.clust.cov.100.women.40.50.M.40.50.cov.70)
# M.40.50.F.15.25
error.infer.clust.cov.100.men.40.50.F.15.25.cov.70 <- as.numeric(vector.MAR.true.cov.100.prop.men40.50.F.15.25) - as.numeric(vector.MAR.cov.70.cl.prop.men40.50.F.15.25)
RMSE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.70 <- RMSE(error.infer.clust.cov.100.men.40.50.F.15.25.cov.70)
MAE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.70 <- MAE(error.infer.clust.cov.100.men.40.50.F.15.25.cov.70)
ARMSE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.70 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men40.50.F.15.25, v2=vector.MAR.cov.70.cl.prop.men40.50.F.15.25)
MRE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.70 <- MRE(error.infer.clust.cov.100.men.40.50.F.15.25.cov.70)
# M.40.50.F.25.40
error.infer.clust.cov.100.men.40.50.F.25.40.cov.70 <- as.numeric(vector.MAR.true.cov.100.prop.men40.50.F.25.40) - as.numeric(vector.MAR.cov.70.cl.prop.men40.50.F.25.40)
RMSE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.70 <- RMSE(error.infer.clust.cov.100.men.40.50.F.25.40.cov.70)
MAE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.70 <- MAE(error.infer.clust.cov.100.men.40.50.F.25.40.cov.70)
ARMSE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.70 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men40.50.F.25.40, v2=vector.MAR.cov.70.cl.prop.men40.50.F.25.40)
MRE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.70 <- MRE(error.infer.clust.cov.100.men.40.50.F.25.40.cov.70)
# F.40.50.M.15.25
error.infer.clust.cov.100.women.40.50.M.15.25.cov.70 <- as.numeric(vector.MAR.true.cov.100.prop.women40.50.M.15.25) - as.numeric(vector.MAR.cov.70.cl.prop.women40.50.M.15.25)
RMSE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.70 <- RMSE(error.infer.clust.cov.100.women.40.50.M.15.25.cov.70)
MAE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.70 <- MAE(error.infer.clust.cov.100.women.40.50.M.15.25.cov.70)
ARMSE.error.infer.clust.cov.100.women.cov.70 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women40.50.M.15.25, v2=vector.MAR.cov.70.cl.prop.women40.50.M.15.25)
MRE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.70 <- MRE(error.infer.clust.cov.100.women.40.50.M.15.25.cov.70)
# F.40.50.M.25.40
error.infer.clust.cov.100.women.40.50.M.25.40.cov.70 <- as.numeric(vector.MAR.true.cov.100.prop.women40.50.M.25.40) - as.numeric(vector.MAR.cov.70.cl.prop.women40.50.M.25.40)
RMSE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.70 <- RMSE(error.infer.clust.cov.100.women.40.50.M.25.40.cov.70)
MAE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.70 <- MAE(error.infer.clust.cov.100.women.40.50.M.25.40.cov.70)
ARMSE.error.infer.clust.cov.100.women.cov.70 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women40.50.M.25.40, v2=vector.MAR.cov.70.cl.prop.women40.50.M.25.40)
MRE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.70 <- MRE(error.infer.clust.cov.100.women.40.50.M.25.40.cov.70)
# Cov 75
# 15.25
# M.15.25.F.15.25
error.infer.clust.cov.100.men.15.25.F.15.25.cov.75 <- as.numeric(vector.MAR.true.cov.100.prop.men15.25.F.15.25) - as.numeric(vector.MAR.cov.75.cl.prop.men15.25.F.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.F.15.25.cov.75 <- RMSE(error.infer.clust.cov.100.men.15.25.F.15.25.cov.75)
MAE.error.infer.clust.cov.100.men.15.25cov.35 <- MAE(error.infer.clust.cov.100.men.15.25.F.15.25.cov.75)
ARMSE.error.infer.clust.cov.100.men.15.25cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men15.25.F.15.25, v2=vector.MAR.cov.75.cl.prop.men15.25.F.15.25)
MRE.error.infer.clust.cov.100.men.15.25.F.15.25.cov.75 <- MRE(error.infer.clust.cov.100.men.15.25.F.15.25.cov.75)
# F.15.25.M.15.25
error.infer.clust.cov.100.women.15.25.M.15.25.cov.75 <- as.numeric(vector.MAR.true.cov.100.prop.women15.25.M.15.25) - as.numeric(vector.MAR.cov.75.cl.prop.women15.25.M.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.75 <- RMSE(error.infer.clust.cov.100.women.15.25.M.15.25.cov.75)
MAE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.75 <- MAE(error.infer.clust.cov.100.women.15.25.M.15.25.cov.75)
ARMSE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.75 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women15.25.M.15.25, v2=vector.MAR.cov.75.cl.prop.women15.25.M.15.25)
MRE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.75 <- MRE(error.infer.clust.cov.100.women.15.25.M.15.25.cov.75)
# M.15.25.F.25.40
error.infer.clust.cov.100.men.15.25.F.25.40.cov.75 <- as.numeric(vector.MAR.true.cov.100.prop.men15.25.F.25.40) - as.numeric(vector.MAR.cov.75.cl.prop.men15.25.F.25.40)
RMSE.error.infer.clust.cov.100.men.15.25.F.25.40.cov.75 <- RMSE(error.infer.clust.cov.100.men.15.25.F.25.40.cov.75)
MAE.error.infer.clust.cov.100.men.15.25cov.35 <- MAE(error.infer.clust.cov.100.men.15.25.F.25.40.cov.75)
ARMSE.error.infer.clust.cov.100.men.15.25cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men15.25.F.25.40, v2=vector.MAR.cov.75.cl.prop.men15.25.F.25.40)
MRE.error.infer.clust.cov.100.men.15.25.F.25.40.cov.75 <- MRE(error.infer.clust.cov.100.men.15.25.F.25.40.cov.75)
# M.15.25.F.40.50
error.infer.clust.cov.100.men.15.25.F.40.50.cov.75 <- as.numeric(vector.MAR.true.cov.100.prop.men15.25.F.40.50) - as.numeric(vector.MAR.cov.75.cl.prop.men15.25.F.40.50)
RMSE.error.infer.clust.cov.100.men.15.25.F.40.50.cov.75 <- RMSE(error.infer.clust.cov.100.men.15.25.F.40.50.cov.75)
MAE.error.infer.clust.cov.100.men.15.25cov.35 <- MAE(error.infer.clust.cov.100.men.15.25.F.40.50.cov.75)
ARMSE.error.infer.clust.cov.100.men.15.25cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men15.25.F.40.50, v2=vector.MAR.cov.75.cl.prop.men15.25.F.40.50)
MRE.error.infer.clust.cov.100.men.15.25.F.40.50.cov.75 <- MRE(error.infer.clust.cov.100.men.15.25.F.40.50.cov.75)
# F.15.25.M.25.40
error.infer.clust.cov.100.women.15.25.M.25.40.cov.75 <- as.numeric(vector.MAR.true.cov.100.prop.women15.25.M.25.40) - as.numeric(vector.MAR.cov.75.cl.prop.women15.25.M.25.40)
RMSE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.75 <- RMSE(error.infer.clust.cov.100.women.15.25.M.25.40.cov.75)
MAE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.75 <- MAE(error.infer.clust.cov.100.women.15.25.M.25.40.cov.75)
ARMSE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.75 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women15.25.M.25.40, v2=vector.MAR.cov.75.cl.prop.women15.25.M.25.40)
MRE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.75 <- MRE(error.infer.clust.cov.100.women.15.25.M.25.40.cov.75)
# F.15.25.M.40.50
error.infer.clust.cov.100.women.15.25.M.40.50.cov.75 <- as.numeric(vector.MAR.true.cov.100.prop.women15.25.M.40.50) - as.numeric(vector.MAR.cov.75.cl.prop.women15.25.M.40.50)
RMSE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.75 <- RMSE(error.infer.clust.cov.100.women.15.25.M.40.50.cov.75)
MAE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.75 <- MAE(error.infer.clust.cov.100.women.15.25.M.40.50.cov.75)
ARMSE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.75 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women15.25.M.40.50, v2=vector.MAR.cov.75.cl.prop.women15.25.M.40.50)
MRE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.75 <- MRE(error.infer.clust.cov.100.women.15.25.M.40.50.cov.75)
# 25.40
# M.25.40.F.25.40
error.infer.clust.cov.100.men.25.40.F.25.40.cov.75 <- as.numeric(vector.MAR.true.cov.100.prop.men25.40.F.25.40) - as.numeric(vector.MAR.cov.75.cl.prop.men25.40.F.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.75 <- RMSE(error.infer.clust.cov.100.men.25.40.F.25.40.cov.75)
MAE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.75 <- MAE(error.infer.clust.cov.100.men.25.40.F.25.40.cov.75)
ARMSE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.75 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men25.40.F.25.40, v2=vector.MAR.cov.75.cl.prop.men25.40.F.25.40)
MRE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.75 <- MRE(error.infer.clust.cov.100.men.25.40.F.25.40.cov.75)
# F.25.40.M.25.40
error.infer.clust.cov.100.women.25.40.M.25.40.cov.75 <- as.numeric(vector.MAR.true.cov.100.prop.women25.40.M.25.40) - as.numeric(vector.MAR.cov.75.cl.prop.women25.40.M.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.75 <- RMSE(error.infer.clust.cov.100.women.25.40.M.25.40.cov.75)
MAE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.75 <- MAE(error.infer.clust.cov.100.women.25.40.M.25.40.cov.75)
ARMSE.error.infer.clust.cov.100.women.cov.75 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women25.40.M.25.40, v2=vector.MAR.cov.75.cl.prop.women25.40.M.25.40)
MRE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.75 <- MRE(error.infer.clust.cov.100.women.25.40.M.25.40.cov.75)
# M.25.40.F.15.25
error.infer.clust.cov.100.men.25.40.F.15.25.cov.75 <- as.numeric(vector.MAR.true.cov.100.prop.men25.40.F.15.25) - as.numeric(vector.MAR.cov.75.cl.prop.men25.40.F.15.25)
RMSE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.75 <- RMSE(error.infer.clust.cov.100.men.25.40.F.15.25.cov.75)
MAE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.75 <- MAE(error.infer.clust.cov.100.men.25.40.F.15.25.cov.75)
ARMSE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.75 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men25.40.F.15.25, v2=vector.MAR.cov.75.cl.prop.men25.40.F.15.25)
MRE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.75 <- MRE(error.infer.clust.cov.100.men.25.40.F.15.25.cov.75)
# M.25.40.F.40.50
error.infer.clust.cov.100.men.25.40.F.40.50.cov.75 <- as.numeric(vector.MAR.true.cov.100.prop.men25.40.F.40.50) - as.numeric(vector.MAR.cov.75.cl.prop.men25.40.F.40.50)
RMSE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.75 <- RMSE(error.infer.clust.cov.100.men.25.40.F.40.50.cov.75)
MAE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.75 <- MAE(error.infer.clust.cov.100.men.25.40.F.40.50.cov.75)
ARMSE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.75 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men25.40.F.40.50, v2=vector.MAR.cov.75.cl.prop.men25.40.F.40.50)
MRE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.75 <- MRE(error.infer.clust.cov.100.men.25.40.F.40.50.cov.75)
# F.25.40.M.15.25
error.infer.clust.cov.100.women.25.40.M.15.25.cov.75 <- as.numeric(vector.MAR.true.cov.100.prop.women25.40.M.15.25) - as.numeric(vector.MAR.cov.75.cl.prop.women25.40.M.15.25)
RMSE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.75 <- RMSE(error.infer.clust.cov.100.women.25.40.M.15.25.cov.75)
MAE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.75 <- MAE(error.infer.clust.cov.100.women.25.40.M.15.25.cov.75)
ARMSE.error.infer.clust.cov.100.women.cov.75 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women25.40.M.15.25, v2=vector.MAR.cov.75.cl.prop.women25.40.M.15.25)
MRE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.75 <- MRE(error.infer.clust.cov.100.women.25.40.M.15.25.cov.75)
# F.25.40.M.40.50
error.infer.clust.cov.100.women.25.40.M.40.50.cov.75 <- as.numeric(vector.MAR.true.cov.100.prop.women25.40.M.40.50) - as.numeric(vector.MAR.cov.75.cl.prop.women25.40.M.40.50)
RMSE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.75 <- RMSE(error.infer.clust.cov.100.women.25.40.M.40.50.cov.75)
MAE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.75 <- MAE(error.infer.clust.cov.100.women.25.40.M.40.50.cov.75)
ARMSE.error.infer.clust.cov.100.women.cov.75 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women25.40.M.40.50, v2=vector.MAR.cov.75.cl.prop.women25.40.M.40.50)
MRE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.75 <- MRE(error.infer.clust.cov.100.women.25.40.M.40.50.cov.75)
# 40.50
# M.40.50.F.40.50
error.infer.clust.cov.100.men.40.50.F.40.50.cov.75 <- as.numeric(vector.MAR.true.cov.100.prop.men40.50.F.40.50) - as.numeric(vector.MAR.cov.75.cl.prop.men40.50.F.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.75 <- RMSE(error.infer.clust.cov.100.men.40.50.F.40.50.cov.75)
MAE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.75 <- MAE(error.infer.clust.cov.100.men.40.50.F.40.50.cov.75)
ARMSE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.75 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men40.50.F.40.50, v2=vector.MAR.cov.75.cl.prop.men40.50.F.40.50)
MRE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.75 <- MRE(error.infer.clust.cov.100.men.40.50.F.40.50.cov.75)
# F.40.50.M.40.50
error.infer.clust.cov.100.women.40.50.M.40.50.cov.75 <- as.numeric(vector.MAR.true.cov.100.prop.women40.50.M.40.50) - as.numeric(vector.MAR.cov.75.cl.prop.women40.50.M.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.75 <- RMSE(error.infer.clust.cov.100.women.40.50.M.40.50.cov.75)
MAE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.75 <- MAE(error.infer.clust.cov.100.women.40.50.M.40.50.cov.75)
ARMSE.error.infer.clust.cov.100.women.cov.75 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women40.50.M.40.50, v2=vector.MAR.cov.75.cl.prop.women40.50.M.40.50)
MRE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.75 <- MRE(error.infer.clust.cov.100.women.40.50.M.40.50.cov.75)
# M.40.50.F.15.25
error.infer.clust.cov.100.men.40.50.F.15.25.cov.75 <- as.numeric(vector.MAR.true.cov.100.prop.men40.50.F.15.25) - as.numeric(vector.MAR.cov.75.cl.prop.men40.50.F.15.25)
RMSE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.75 <- RMSE(error.infer.clust.cov.100.men.40.50.F.15.25.cov.75)
MAE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.75 <- MAE(error.infer.clust.cov.100.men.40.50.F.15.25.cov.75)
ARMSE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.75 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men40.50.F.15.25, v2=vector.MAR.cov.75.cl.prop.men40.50.F.15.25)
MRE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.75 <- MRE(error.infer.clust.cov.100.men.40.50.F.15.25.cov.75)
# M.40.50.F.25.40
error.infer.clust.cov.100.men.40.50.F.25.40.cov.75 <- as.numeric(vector.MAR.true.cov.100.prop.men40.50.F.25.40) - as.numeric(vector.MAR.cov.75.cl.prop.men40.50.F.25.40)
RMSE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.75 <- RMSE(error.infer.clust.cov.100.men.40.50.F.25.40.cov.75)
MAE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.75 <- MAE(error.infer.clust.cov.100.men.40.50.F.25.40.cov.75)
ARMSE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.75 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men40.50.F.25.40, v2=vector.MAR.cov.75.cl.prop.men40.50.F.25.40)
MRE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.75 <- MRE(error.infer.clust.cov.100.men.40.50.F.25.40.cov.75)
# F.40.50.M.15.25
error.infer.clust.cov.100.women.40.50.M.15.25.cov.75 <- as.numeric(vector.MAR.true.cov.100.prop.women40.50.M.15.25) - as.numeric(vector.MAR.cov.75.cl.prop.women40.50.M.15.25)
RMSE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.75 <- RMSE(error.infer.clust.cov.100.women.40.50.M.15.25.cov.75)
MAE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.75 <- MAE(error.infer.clust.cov.100.women.40.50.M.15.25.cov.75)
ARMSE.error.infer.clust.cov.100.women.cov.75 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women40.50.M.15.25, v2=vector.MAR.cov.75.cl.prop.women40.50.M.15.25)
MRE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.75 <- MRE(error.infer.clust.cov.100.women.40.50.M.15.25.cov.75)
# F.40.50.M.25.40
error.infer.clust.cov.100.women.40.50.M.25.40.cov.75 <- as.numeric(vector.MAR.true.cov.100.prop.women40.50.M.25.40) - as.numeric(vector.MAR.cov.75.cl.prop.women40.50.M.25.40)
RMSE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.75 <- RMSE(error.infer.clust.cov.100.women.40.50.M.25.40.cov.75)
MAE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.75 <- MAE(error.infer.clust.cov.100.women.40.50.M.25.40.cov.75)
ARMSE.error.infer.clust.cov.100.women.cov.75 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women40.50.M.25.40, v2=vector.MAR.cov.75.cl.prop.women40.50.M.25.40)
MRE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.75 <- MRE(error.infer.clust.cov.100.women.40.50.M.25.40.cov.75)
# Cov 80
# 15.25
# M.15.25.F.15.25
error.infer.clust.cov.100.men.15.25.F.15.25.cov.80 <- as.numeric(vector.MAR.true.cov.100.prop.men15.25.F.15.25) - as.numeric(vector.MAR.cov.80.cl.prop.men15.25.F.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.F.15.25.cov.80 <- RMSE(error.infer.clust.cov.100.men.15.25.F.15.25.cov.80)
MAE.error.infer.clust.cov.100.men.15.25cov.35 <- MAE(error.infer.clust.cov.100.men.15.25.F.15.25.cov.80)
ARMSE.error.infer.clust.cov.100.men.15.25cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men15.25.F.15.25, v2=vector.MAR.cov.80.cl.prop.men15.25.F.15.25)
MRE.error.infer.clust.cov.100.men.15.25.F.15.25.cov.80 <- MRE(error.infer.clust.cov.100.men.15.25.F.15.25.cov.80)
# F.15.25.M.15.25
error.infer.clust.cov.100.women.15.25.M.15.25.cov.80 <- as.numeric(vector.MAR.true.cov.100.prop.women15.25.M.15.25) - as.numeric(vector.MAR.cov.80.cl.prop.women15.25.M.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.80 <- RMSE(error.infer.clust.cov.100.women.15.25.M.15.25.cov.80)
MAE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.80 <- MAE(error.infer.clust.cov.100.women.15.25.M.15.25.cov.80)
ARMSE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.80 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women15.25.M.15.25, v2=vector.MAR.cov.80.cl.prop.women15.25.M.15.25)
MRE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.80 <- MRE(error.infer.clust.cov.100.women.15.25.M.15.25.cov.80)
# M.15.25.F.25.40
error.infer.clust.cov.100.men.15.25.F.25.40.cov.80 <- as.numeric(vector.MAR.true.cov.100.prop.men15.25.F.25.40) - as.numeric(vector.MAR.cov.80.cl.prop.men15.25.F.25.40)
RMSE.error.infer.clust.cov.100.men.15.25.F.25.40.cov.80 <- RMSE(error.infer.clust.cov.100.men.15.25.F.25.40.cov.80)
MAE.error.infer.clust.cov.100.men.15.25cov.35 <- MAE(error.infer.clust.cov.100.men.15.25.F.25.40.cov.80)
ARMSE.error.infer.clust.cov.100.men.15.25cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men15.25.F.25.40, v2=vector.MAR.cov.80.cl.prop.men15.25.F.25.40)
MRE.error.infer.clust.cov.100.men.15.25.F.25.40.cov.80 <- MRE(error.infer.clust.cov.100.men.15.25.F.25.40.cov.80)
# M.15.25.F.40.50
error.infer.clust.cov.100.men.15.25.F.40.50.cov.80 <- as.numeric(vector.MAR.true.cov.100.prop.men15.25.F.40.50) - as.numeric(vector.MAR.cov.80.cl.prop.men15.25.F.40.50)
RMSE.error.infer.clust.cov.100.men.15.25.F.40.50.cov.80 <- RMSE(error.infer.clust.cov.100.men.15.25.F.40.50.cov.80)
MAE.error.infer.clust.cov.100.men.15.25cov.35 <- MAE(error.infer.clust.cov.100.men.15.25.F.40.50.cov.80)
ARMSE.error.infer.clust.cov.100.men.15.25cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men15.25.F.40.50, v2=vector.MAR.cov.80.cl.prop.men15.25.F.40.50)
MRE.error.infer.clust.cov.100.men.15.25.F.40.50.cov.80 <- MRE(error.infer.clust.cov.100.men.15.25.F.40.50.cov.80)
# F.15.25.M.25.40
error.infer.clust.cov.100.women.15.25.M.25.40.cov.80 <- as.numeric(vector.MAR.true.cov.100.prop.women15.25.M.25.40) - as.numeric(vector.MAR.cov.80.cl.prop.women15.25.M.25.40)
RMSE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.80 <- RMSE(error.infer.clust.cov.100.women.15.25.M.25.40.cov.80)
MAE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.80 <- MAE(error.infer.clust.cov.100.women.15.25.M.25.40.cov.80)
ARMSE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.80 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women15.25.M.25.40, v2=vector.MAR.cov.80.cl.prop.women15.25.M.25.40)
MRE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.80 <- MRE(error.infer.clust.cov.100.women.15.25.M.25.40.cov.80)
# F.15.25.M.40.50
error.infer.clust.cov.100.women.15.25.M.40.50.cov.80 <- as.numeric(vector.MAR.true.cov.100.prop.women15.25.M.40.50) - as.numeric(vector.MAR.cov.80.cl.prop.women15.25.M.40.50)
RMSE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.80 <- RMSE(error.infer.clust.cov.100.women.15.25.M.40.50.cov.80)
MAE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.80 <- MAE(error.infer.clust.cov.100.women.15.25.M.40.50.cov.80)
ARMSE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.80 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women15.25.M.40.50, v2=vector.MAR.cov.80.cl.prop.women15.25.M.40.50)
MRE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.80 <- MRE(error.infer.clust.cov.100.women.15.25.M.40.50.cov.80)
# 25.40
# M.25.40.F.25.40
error.infer.clust.cov.100.men.25.40.F.25.40.cov.80 <- as.numeric(vector.MAR.true.cov.100.prop.men25.40.F.25.40) - as.numeric(vector.MAR.cov.80.cl.prop.men25.40.F.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.80 <- RMSE(error.infer.clust.cov.100.men.25.40.F.25.40.cov.80)
MAE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.80 <- MAE(error.infer.clust.cov.100.men.25.40.F.25.40.cov.80)
ARMSE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.80 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men25.40.F.25.40, v2=vector.MAR.cov.80.cl.prop.men25.40.F.25.40)
MRE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.80 <- MRE(error.infer.clust.cov.100.men.25.40.F.25.40.cov.80)
# F.25.40.M.25.40
error.infer.clust.cov.100.women.25.40.M.25.40.cov.80 <- as.numeric(vector.MAR.true.cov.100.prop.women25.40.M.25.40) - as.numeric(vector.MAR.cov.80.cl.prop.women25.40.M.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.80 <- RMSE(error.infer.clust.cov.100.women.25.40.M.25.40.cov.80)
MAE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.80 <- MAE(error.infer.clust.cov.100.women.25.40.M.25.40.cov.80)
ARMSE.error.infer.clust.cov.100.women.cov.80 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women25.40.M.25.40, v2=vector.MAR.cov.80.cl.prop.women25.40.M.25.40)
MRE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.80 <- MRE(error.infer.clust.cov.100.women.25.40.M.25.40.cov.80)
# M.25.40.F.15.25
error.infer.clust.cov.100.men.25.40.F.15.25.cov.80 <- as.numeric(vector.MAR.true.cov.100.prop.men25.40.F.15.25) - as.numeric(vector.MAR.cov.80.cl.prop.men25.40.F.15.25)
RMSE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.80 <- RMSE(error.infer.clust.cov.100.men.25.40.F.15.25.cov.80)
MAE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.80 <- MAE(error.infer.clust.cov.100.men.25.40.F.15.25.cov.80)
ARMSE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.80 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men25.40.F.15.25, v2=vector.MAR.cov.80.cl.prop.men25.40.F.15.25)
MRE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.80 <- MRE(error.infer.clust.cov.100.men.25.40.F.15.25.cov.80)
# M.25.40.F.40.50
error.infer.clust.cov.100.men.25.40.F.40.50.cov.80 <- as.numeric(vector.MAR.true.cov.100.prop.men25.40.F.40.50) - as.numeric(vector.MAR.cov.80.cl.prop.men25.40.F.40.50)
RMSE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.80 <- RMSE(error.infer.clust.cov.100.men.25.40.F.40.50.cov.80)
MAE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.80 <- MAE(error.infer.clust.cov.100.men.25.40.F.40.50.cov.80)
ARMSE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.80 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men25.40.F.40.50, v2=vector.MAR.cov.80.cl.prop.men25.40.F.40.50)
MRE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.80 <- MRE(error.infer.clust.cov.100.men.25.40.F.40.50.cov.80)
# F.25.40.M.15.25
error.infer.clust.cov.100.women.25.40.M.15.25.cov.80 <- as.numeric(vector.MAR.true.cov.100.prop.women25.40.M.15.25) - as.numeric(vector.MAR.cov.80.cl.prop.women25.40.M.15.25)
RMSE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.80 <- RMSE(error.infer.clust.cov.100.women.25.40.M.15.25.cov.80)
MAE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.80 <- MAE(error.infer.clust.cov.100.women.25.40.M.15.25.cov.80)
ARMSE.error.infer.clust.cov.100.women.cov.80 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women25.40.M.15.25, v2=vector.MAR.cov.80.cl.prop.women25.40.M.15.25)
MRE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.80 <- MRE(error.infer.clust.cov.100.women.25.40.M.15.25.cov.80)
# F.25.40.M.40.50
error.infer.clust.cov.100.women.25.40.M.40.50.cov.80 <- as.numeric(vector.MAR.true.cov.100.prop.women25.40.M.40.50) - as.numeric(vector.MAR.cov.80.cl.prop.women25.40.M.40.50)
RMSE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.80 <- RMSE(error.infer.clust.cov.100.women.25.40.M.40.50.cov.80)
MAE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.80 <- MAE(error.infer.clust.cov.100.women.25.40.M.40.50.cov.80)
ARMSE.error.infer.clust.cov.100.women.cov.80 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women25.40.M.40.50, v2=vector.MAR.cov.80.cl.prop.women25.40.M.40.50)
MRE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.80 <- MRE(error.infer.clust.cov.100.women.25.40.M.40.50.cov.80)
# 40.50
# M.40.50.F.40.50
error.infer.clust.cov.100.men.40.50.F.40.50.cov.80 <- as.numeric(vector.MAR.true.cov.100.prop.men40.50.F.40.50) - as.numeric(vector.MAR.cov.80.cl.prop.men40.50.F.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.80 <- RMSE(error.infer.clust.cov.100.men.40.50.F.40.50.cov.80)
MAE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.80 <- MAE(error.infer.clust.cov.100.men.40.50.F.40.50.cov.80)
ARMSE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.80 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men40.50.F.40.50, v2=vector.MAR.cov.80.cl.prop.men40.50.F.40.50)
MRE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.80 <- MRE(error.infer.clust.cov.100.men.40.50.F.40.50.cov.80)
# F.40.50.M.40.50
error.infer.clust.cov.100.women.40.50.M.40.50.cov.80 <- as.numeric(vector.MAR.true.cov.100.prop.women40.50.M.40.50) - as.numeric(vector.MAR.cov.80.cl.prop.women40.50.M.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.80 <- RMSE(error.infer.clust.cov.100.women.40.50.M.40.50.cov.80)
MAE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.80 <- MAE(error.infer.clust.cov.100.women.40.50.M.40.50.cov.80)
ARMSE.error.infer.clust.cov.100.women.cov.80 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women40.50.M.40.50, v2=vector.MAR.cov.80.cl.prop.women40.50.M.40.50)
MRE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.80 <- MRE(error.infer.clust.cov.100.women.40.50.M.40.50.cov.80)
# M.40.50.F.15.25
error.infer.clust.cov.100.men.40.50.F.15.25.cov.80 <- as.numeric(vector.MAR.true.cov.100.prop.men40.50.F.15.25) - as.numeric(vector.MAR.cov.80.cl.prop.men40.50.F.15.25)
RMSE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.80 <- RMSE(error.infer.clust.cov.100.men.40.50.F.15.25.cov.80)
MAE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.80 <- MAE(error.infer.clust.cov.100.men.40.50.F.15.25.cov.80)
ARMSE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.80 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men40.50.F.15.25, v2=vector.MAR.cov.80.cl.prop.men40.50.F.15.25)
MRE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.80 <- MRE(error.infer.clust.cov.100.men.40.50.F.15.25.cov.80)
# M.40.50.F.25.40
error.infer.clust.cov.100.men.40.50.F.25.40.cov.80 <- as.numeric(vector.MAR.true.cov.100.prop.men40.50.F.25.40) - as.numeric(vector.MAR.cov.80.cl.prop.men40.50.F.25.40)
RMSE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.80 <- RMSE(error.infer.clust.cov.100.men.40.50.F.25.40.cov.80)
MAE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.80 <- MAE(error.infer.clust.cov.100.men.40.50.F.25.40.cov.80)
ARMSE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.80 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men40.50.F.25.40, v2=vector.MAR.cov.80.cl.prop.men40.50.F.25.40)
MRE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.80 <- MRE(error.infer.clust.cov.100.men.40.50.F.25.40.cov.80)
# F.40.50.M.15.25
error.infer.clust.cov.100.women.40.50.M.15.25.cov.80 <- as.numeric(vector.MAR.true.cov.100.prop.women40.50.M.15.25) - as.numeric(vector.MAR.cov.80.cl.prop.women40.50.M.15.25)
RMSE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.80 <- RMSE(error.infer.clust.cov.100.women.40.50.M.15.25.cov.80)
MAE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.80 <- MAE(error.infer.clust.cov.100.women.40.50.M.15.25.cov.80)
ARMSE.error.infer.clust.cov.100.women.cov.80 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women40.50.M.15.25, v2=vector.MAR.cov.80.cl.prop.women40.50.M.15.25)
MRE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.80 <- MRE(error.infer.clust.cov.100.women.40.50.M.15.25.cov.80)
# F.40.50.M.25.40
error.infer.clust.cov.100.women.40.50.M.25.40.cov.80 <- as.numeric(vector.MAR.true.cov.100.prop.women40.50.M.25.40) - as.numeric(vector.MAR.cov.80.cl.prop.women40.50.M.25.40)
RMSE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.80 <- RMSE(error.infer.clust.cov.100.women.40.50.M.25.40.cov.80)
MAE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.80 <- MAE(error.infer.clust.cov.100.women.40.50.M.25.40.cov.80)
ARMSE.error.infer.clust.cov.100.women.cov.80 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women40.50.M.25.40, v2=vector.MAR.cov.80.cl.prop.women40.50.M.25.40)
MRE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.80 <- MRE(error.infer.clust.cov.100.women.40.50.M.25.40.cov.80)
# Cov 85
# 15.25
# M.15.25.F.15.25
error.infer.clust.cov.100.men.15.25.F.15.25.cov.85 <- as.numeric(vector.MAR.true.cov.100.prop.men15.25.F.15.25) - as.numeric(vector.MAR.cov.85.cl.prop.men15.25.F.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.F.15.25.cov.85 <- RMSE(error.infer.clust.cov.100.men.15.25.F.15.25.cov.85)
MAE.error.infer.clust.cov.100.men.15.25cov.35 <- MAE(error.infer.clust.cov.100.men.15.25.F.15.25.cov.85)
ARMSE.error.infer.clust.cov.100.men.15.25cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men15.25.F.15.25, v2=vector.MAR.cov.85.cl.prop.men15.25.F.15.25)
MRE.error.infer.clust.cov.100.men.15.25.F.15.25.cov.85 <- MRE(error.infer.clust.cov.100.men.15.25.F.15.25.cov.85)
# F.15.25.M.15.25
error.infer.clust.cov.100.women.15.25.M.15.25.cov.85 <- as.numeric(vector.MAR.true.cov.100.prop.women15.25.M.15.25) - as.numeric(vector.MAR.cov.85.cl.prop.women15.25.M.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.85 <- RMSE(error.infer.clust.cov.100.women.15.25.M.15.25.cov.85)
MAE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.85 <- MAE(error.infer.clust.cov.100.women.15.25.M.15.25.cov.85)
ARMSE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.85 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women15.25.M.15.25, v2=vector.MAR.cov.85.cl.prop.women15.25.M.15.25)
MRE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.85 <- MRE(error.infer.clust.cov.100.women.15.25.M.15.25.cov.85)
# M.15.25.F.25.40
error.infer.clust.cov.100.men.15.25.F.25.40.cov.85 <- as.numeric(vector.MAR.true.cov.100.prop.men15.25.F.25.40) - as.numeric(vector.MAR.cov.85.cl.prop.men15.25.F.25.40)
RMSE.error.infer.clust.cov.100.men.15.25.F.25.40.cov.85 <- RMSE(error.infer.clust.cov.100.men.15.25.F.25.40.cov.85)
MAE.error.infer.clust.cov.100.men.15.25cov.35 <- MAE(error.infer.clust.cov.100.men.15.25.F.25.40.cov.85)
ARMSE.error.infer.clust.cov.100.men.15.25cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men15.25.F.25.40, v2=vector.MAR.cov.85.cl.prop.men15.25.F.25.40)
MRE.error.infer.clust.cov.100.men.15.25.F.25.40.cov.85 <- MRE(error.infer.clust.cov.100.men.15.25.F.25.40.cov.85)
# M.15.25.F.40.50
error.infer.clust.cov.100.men.15.25.F.40.50.cov.85 <- as.numeric(vector.MAR.true.cov.100.prop.men15.25.F.40.50) - as.numeric(vector.MAR.cov.85.cl.prop.men15.25.F.40.50)
RMSE.error.infer.clust.cov.100.men.15.25.F.40.50.cov.85 <- RMSE(error.infer.clust.cov.100.men.15.25.F.40.50.cov.85)
MAE.error.infer.clust.cov.100.men.15.25cov.35 <- MAE(error.infer.clust.cov.100.men.15.25.F.40.50.cov.85)
ARMSE.error.infer.clust.cov.100.men.15.25cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men15.25.F.40.50, v2=vector.MAR.cov.85.cl.prop.men15.25.F.40.50)
MRE.error.infer.clust.cov.100.men.15.25.F.40.50.cov.85 <- MRE(error.infer.clust.cov.100.men.15.25.F.40.50.cov.85)
# F.15.25.M.25.40
error.infer.clust.cov.100.women.15.25.M.25.40.cov.85 <- as.numeric(vector.MAR.true.cov.100.prop.women15.25.M.25.40) - as.numeric(vector.MAR.cov.85.cl.prop.women15.25.M.25.40)
RMSE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.85 <- RMSE(error.infer.clust.cov.100.women.15.25.M.25.40.cov.85)
MAE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.85 <- MAE(error.infer.clust.cov.100.women.15.25.M.25.40.cov.85)
ARMSE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.85 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women15.25.M.25.40, v2=vector.MAR.cov.85.cl.prop.women15.25.M.25.40)
MRE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.85 <- MRE(error.infer.clust.cov.100.women.15.25.M.25.40.cov.85)
# F.15.25.M.40.50
error.infer.clust.cov.100.women.15.25.M.40.50.cov.85 <- as.numeric(vector.MAR.true.cov.100.prop.women15.25.M.40.50) - as.numeric(vector.MAR.cov.85.cl.prop.women15.25.M.40.50)
RMSE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.85 <- RMSE(error.infer.clust.cov.100.women.15.25.M.40.50.cov.85)
MAE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.85 <- MAE(error.infer.clust.cov.100.women.15.25.M.40.50.cov.85)
ARMSE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.85 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women15.25.M.40.50, v2=vector.MAR.cov.85.cl.prop.women15.25.M.40.50)
MRE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.85 <- MRE(error.infer.clust.cov.100.women.15.25.M.40.50.cov.85)
# 25.40
# M.25.40.F.25.40
error.infer.clust.cov.100.men.25.40.F.25.40.cov.85 <- as.numeric(vector.MAR.true.cov.100.prop.men25.40.F.25.40) - as.numeric(vector.MAR.cov.85.cl.prop.men25.40.F.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.85 <- RMSE(error.infer.clust.cov.100.men.25.40.F.25.40.cov.85)
MAE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.85 <- MAE(error.infer.clust.cov.100.men.25.40.F.25.40.cov.85)
ARMSE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.85 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men25.40.F.25.40, v2=vector.MAR.cov.85.cl.prop.men25.40.F.25.40)
MRE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.85 <- MRE(error.infer.clust.cov.100.men.25.40.F.25.40.cov.85)
# F.25.40.M.25.40
error.infer.clust.cov.100.women.25.40.M.25.40.cov.85 <- as.numeric(vector.MAR.true.cov.100.prop.women25.40.M.25.40) - as.numeric(vector.MAR.cov.85.cl.prop.women25.40.M.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.85 <- RMSE(error.infer.clust.cov.100.women.25.40.M.25.40.cov.85)
MAE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.85 <- MAE(error.infer.clust.cov.100.women.25.40.M.25.40.cov.85)
ARMSE.error.infer.clust.cov.100.women.cov.85 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women25.40.M.25.40, v2=vector.MAR.cov.85.cl.prop.women25.40.M.25.40)
MRE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.85 <- MRE(error.infer.clust.cov.100.women.25.40.M.25.40.cov.85)
# M.25.40.F.15.25
error.infer.clust.cov.100.men.25.40.F.15.25.cov.85 <- as.numeric(vector.MAR.true.cov.100.prop.men25.40.F.15.25) - as.numeric(vector.MAR.cov.85.cl.prop.men25.40.F.15.25)
RMSE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.85 <- RMSE(error.infer.clust.cov.100.men.25.40.F.15.25.cov.85)
MAE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.85 <- MAE(error.infer.clust.cov.100.men.25.40.F.15.25.cov.85)
ARMSE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.85 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men25.40.F.15.25, v2=vector.MAR.cov.85.cl.prop.men25.40.F.15.25)
MRE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.85 <- MRE(error.infer.clust.cov.100.men.25.40.F.15.25.cov.85)
# M.25.40.F.40.50
error.infer.clust.cov.100.men.25.40.F.40.50.cov.85 <- as.numeric(vector.MAR.true.cov.100.prop.men25.40.F.40.50) - as.numeric(vector.MAR.cov.85.cl.prop.men25.40.F.40.50)
RMSE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.85 <- RMSE(error.infer.clust.cov.100.men.25.40.F.40.50.cov.85)
MAE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.85 <- MAE(error.infer.clust.cov.100.men.25.40.F.40.50.cov.85)
ARMSE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.85 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men25.40.F.40.50, v2=vector.MAR.cov.85.cl.prop.men25.40.F.40.50)
MRE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.85 <- MRE(error.infer.clust.cov.100.men.25.40.F.40.50.cov.85)
# F.25.40.M.15.25
error.infer.clust.cov.100.women.25.40.M.15.25.cov.85 <- as.numeric(vector.MAR.true.cov.100.prop.women25.40.M.15.25) - as.numeric(vector.MAR.cov.85.cl.prop.women25.40.M.15.25)
RMSE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.85 <- RMSE(error.infer.clust.cov.100.women.25.40.M.15.25.cov.85)
MAE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.85 <- MAE(error.infer.clust.cov.100.women.25.40.M.15.25.cov.85)
ARMSE.error.infer.clust.cov.100.women.cov.85 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women25.40.M.15.25, v2=vector.MAR.cov.85.cl.prop.women25.40.M.15.25)
MRE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.85 <- MRE(error.infer.clust.cov.100.women.25.40.M.15.25.cov.85)
# F.25.40.M.40.50
error.infer.clust.cov.100.women.25.40.M.40.50.cov.85 <- as.numeric(vector.MAR.true.cov.100.prop.women25.40.M.40.50) - as.numeric(vector.MAR.cov.85.cl.prop.women25.40.M.40.50)
RMSE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.85 <- RMSE(error.infer.clust.cov.100.women.25.40.M.40.50.cov.85)
MAE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.85 <- MAE(error.infer.clust.cov.100.women.25.40.M.40.50.cov.85)
ARMSE.error.infer.clust.cov.100.women.cov.85 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women25.40.M.40.50, v2=vector.MAR.cov.85.cl.prop.women25.40.M.40.50)
MRE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.85 <- MRE(error.infer.clust.cov.100.women.25.40.M.40.50.cov.85)
# 40.50
# M.40.50.F.40.50
error.infer.clust.cov.100.men.40.50.F.40.50.cov.85 <- as.numeric(vector.MAR.true.cov.100.prop.men40.50.F.40.50) - as.numeric(vector.MAR.cov.85.cl.prop.men40.50.F.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.85 <- RMSE(error.infer.clust.cov.100.men.40.50.F.40.50.cov.85)
MAE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.85 <- MAE(error.infer.clust.cov.100.men.40.50.F.40.50.cov.85)
ARMSE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.85 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men40.50.F.40.50, v2=vector.MAR.cov.85.cl.prop.men40.50.F.40.50)
MRE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.85 <- MRE(error.infer.clust.cov.100.men.40.50.F.40.50.cov.85)
# F.40.50.M.40.50
error.infer.clust.cov.100.women.40.50.M.40.50.cov.85 <- as.numeric(vector.MAR.true.cov.100.prop.women40.50.M.40.50) - as.numeric(vector.MAR.cov.85.cl.prop.women40.50.M.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.85 <- RMSE(error.infer.clust.cov.100.women.40.50.M.40.50.cov.85)
MAE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.85 <- MAE(error.infer.clust.cov.100.women.40.50.M.40.50.cov.85)
ARMSE.error.infer.clust.cov.100.women.cov.85 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women40.50.M.40.50, v2=vector.MAR.cov.85.cl.prop.women40.50.M.40.50)
MRE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.85 <- MRE(error.infer.clust.cov.100.women.40.50.M.40.50.cov.85)
# M.40.50.F.15.25
error.infer.clust.cov.100.men.40.50.F.15.25.cov.85 <- as.numeric(vector.MAR.true.cov.100.prop.men40.50.F.15.25) - as.numeric(vector.MAR.cov.85.cl.prop.men40.50.F.15.25)
RMSE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.85 <- RMSE(error.infer.clust.cov.100.men.40.50.F.15.25.cov.85)
MAE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.85 <- MAE(error.infer.clust.cov.100.men.40.50.F.15.25.cov.85)
ARMSE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.85 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men40.50.F.15.25, v2=vector.MAR.cov.85.cl.prop.men40.50.F.15.25)
MRE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.85 <- MRE(error.infer.clust.cov.100.men.40.50.F.15.25.cov.85)
# M.40.50.F.25.40
error.infer.clust.cov.100.men.40.50.F.25.40.cov.85 <- as.numeric(vector.MAR.true.cov.100.prop.men40.50.F.25.40) - as.numeric(vector.MAR.cov.85.cl.prop.men40.50.F.25.40)
RMSE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.85 <- RMSE(error.infer.clust.cov.100.men.40.50.F.25.40.cov.85)
MAE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.85 <- MAE(error.infer.clust.cov.100.men.40.50.F.25.40.cov.85)
ARMSE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.85 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men40.50.F.25.40, v2=vector.MAR.cov.85.cl.prop.men40.50.F.25.40)
MRE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.85 <- MRE(error.infer.clust.cov.100.men.40.50.F.25.40.cov.85)
# F.40.50.M.15.25
error.infer.clust.cov.100.women.40.50.M.15.25.cov.85 <- as.numeric(vector.MAR.true.cov.100.prop.women40.50.M.15.25) - as.numeric(vector.MAR.cov.85.cl.prop.women40.50.M.15.25)
RMSE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.85 <- RMSE(error.infer.clust.cov.100.women.40.50.M.15.25.cov.85)
MAE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.85 <- MAE(error.infer.clust.cov.100.women.40.50.M.15.25.cov.85)
ARMSE.error.infer.clust.cov.100.women.cov.85 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women40.50.M.15.25, v2=vector.MAR.cov.85.cl.prop.women40.50.M.15.25)
MRE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.85 <- MRE(error.infer.clust.cov.100.women.40.50.M.15.25.cov.85)
# F.40.50.M.25.40
error.infer.clust.cov.100.women.40.50.M.25.40.cov.85 <- as.numeric(vector.MAR.true.cov.100.prop.women40.50.M.25.40) - as.numeric(vector.MAR.cov.85.cl.prop.women40.50.M.25.40)
RMSE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.85 <- RMSE(error.infer.clust.cov.100.women.40.50.M.25.40.cov.85)
MAE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.85 <- MAE(error.infer.clust.cov.100.women.40.50.M.25.40.cov.85)
ARMSE.error.infer.clust.cov.100.women.cov.85 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women40.50.M.25.40, v2=vector.MAR.cov.85.cl.prop.women40.50.M.25.40)
MRE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.85 <- MRE(error.infer.clust.cov.100.women.40.50.M.25.40.cov.85)
# Cov 90
# 15.25
# M.15.25.F.15.25
error.infer.clust.cov.100.men.15.25.F.15.25.cov.90 <- as.numeric(vector.MAR.true.cov.100.prop.men15.25.F.15.25) - as.numeric(vector.MAR.cov.90.cl.prop.men15.25.F.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.F.15.25.cov.90 <- RMSE(error.infer.clust.cov.100.men.15.25.F.15.25.cov.90)
MAE.error.infer.clust.cov.100.men.15.25cov.35 <- MAE(error.infer.clust.cov.100.men.15.25.F.15.25.cov.90)
ARMSE.error.infer.clust.cov.100.men.15.25cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men15.25.F.15.25, v2=vector.MAR.cov.90.cl.prop.men15.25.F.15.25)
MRE.error.infer.clust.cov.100.men.15.25.F.15.25.cov.90 <- MRE(error.infer.clust.cov.100.men.15.25.F.15.25.cov.90)
# F.15.25.M.15.25
error.infer.clust.cov.100.women.15.25.M.15.25.cov.90 <- as.numeric(vector.MAR.true.cov.100.prop.women15.25.M.15.25) - as.numeric(vector.MAR.cov.90.cl.prop.women15.25.M.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.90 <- RMSE(error.infer.clust.cov.100.women.15.25.M.15.25.cov.90)
MAE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.90 <- MAE(error.infer.clust.cov.100.women.15.25.M.15.25.cov.90)
ARMSE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.90 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women15.25.M.15.25, v2=vector.MAR.cov.90.cl.prop.women15.25.M.15.25)
MRE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.90 <- MRE(error.infer.clust.cov.100.women.15.25.M.15.25.cov.90)
# M.15.25.F.25.40
error.infer.clust.cov.100.men.15.25.F.25.40.cov.90 <- as.numeric(vector.MAR.true.cov.100.prop.men15.25.F.25.40) - as.numeric(vector.MAR.cov.90.cl.prop.men15.25.F.25.40)
RMSE.error.infer.clust.cov.100.men.15.25.F.25.40.cov.90 <- RMSE(error.infer.clust.cov.100.men.15.25.F.25.40.cov.90)
MAE.error.infer.clust.cov.100.men.15.25cov.35 <- MAE(error.infer.clust.cov.100.men.15.25.F.25.40.cov.90)
ARMSE.error.infer.clust.cov.100.men.15.25cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men15.25.F.25.40, v2=vector.MAR.cov.90.cl.prop.men15.25.F.25.40)
MRE.error.infer.clust.cov.100.men.15.25.F.25.40.cov.90 <- MRE(error.infer.clust.cov.100.men.15.25.F.25.40.cov.90)
# M.15.25.F.40.50
error.infer.clust.cov.100.men.15.25.F.40.50.cov.90 <- as.numeric(vector.MAR.true.cov.100.prop.men15.25.F.40.50) - as.numeric(vector.MAR.cov.90.cl.prop.men15.25.F.40.50)
RMSE.error.infer.clust.cov.100.men.15.25.F.40.50.cov.90 <- RMSE(error.infer.clust.cov.100.men.15.25.F.40.50.cov.90)
MAE.error.infer.clust.cov.100.men.15.25cov.35 <- MAE(error.infer.clust.cov.100.men.15.25.F.40.50.cov.90)
ARMSE.error.infer.clust.cov.100.men.15.25cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men15.25.F.40.50, v2=vector.MAR.cov.90.cl.prop.men15.25.F.40.50)
MRE.error.infer.clust.cov.100.men.15.25.F.40.50.cov.90 <- MRE(error.infer.clust.cov.100.men.15.25.F.40.50.cov.90)
# F.15.25.M.25.40
error.infer.clust.cov.100.women.15.25.M.25.40.cov.90 <- as.numeric(vector.MAR.true.cov.100.prop.women15.25.M.25.40) - as.numeric(vector.MAR.cov.90.cl.prop.women15.25.M.25.40)
RMSE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.90 <- RMSE(error.infer.clust.cov.100.women.15.25.M.25.40.cov.90)
MAE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.90 <- MAE(error.infer.clust.cov.100.women.15.25.M.25.40.cov.90)
ARMSE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.90 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women15.25.M.25.40, v2=vector.MAR.cov.90.cl.prop.women15.25.M.25.40)
MRE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.90 <- MRE(error.infer.clust.cov.100.women.15.25.M.25.40.cov.90)
# F.15.25.M.40.50
error.infer.clust.cov.100.women.15.25.M.40.50.cov.90 <- as.numeric(vector.MAR.true.cov.100.prop.women15.25.M.40.50) - as.numeric(vector.MAR.cov.90.cl.prop.women15.25.M.40.50)
RMSE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.90 <- RMSE(error.infer.clust.cov.100.women.15.25.M.40.50.cov.90)
MAE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.90 <- MAE(error.infer.clust.cov.100.women.15.25.M.40.50.cov.90)
ARMSE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.90 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women15.25.M.40.50, v2=vector.MAR.cov.90.cl.prop.women15.25.M.40.50)
MRE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.90 <- MRE(error.infer.clust.cov.100.women.15.25.M.40.50.cov.90)
# 25.40
# M.25.40.F.25.40
error.infer.clust.cov.100.men.25.40.F.25.40.cov.90 <- as.numeric(vector.MAR.true.cov.100.prop.men25.40.F.25.40) - as.numeric(vector.MAR.cov.90.cl.prop.men25.40.F.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.90 <- RMSE(error.infer.clust.cov.100.men.25.40.F.25.40.cov.90)
MAE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.90 <- MAE(error.infer.clust.cov.100.men.25.40.F.25.40.cov.90)
ARMSE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.90 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men25.40.F.25.40, v2=vector.MAR.cov.90.cl.prop.men25.40.F.25.40)
MRE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.90 <- MRE(error.infer.clust.cov.100.men.25.40.F.25.40.cov.90)
# F.25.40.M.25.40
error.infer.clust.cov.100.women.25.40.M.25.40.cov.90 <- as.numeric(vector.MAR.true.cov.100.prop.women25.40.M.25.40) - as.numeric(vector.MAR.cov.90.cl.prop.women25.40.M.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.90 <- RMSE(error.infer.clust.cov.100.women.25.40.M.25.40.cov.90)
MAE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.90 <- MAE(error.infer.clust.cov.100.women.25.40.M.25.40.cov.90)
ARMSE.error.infer.clust.cov.100.women.cov.90 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women25.40.M.25.40, v2=vector.MAR.cov.90.cl.prop.women25.40.M.25.40)
MRE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.90 <- MRE(error.infer.clust.cov.100.women.25.40.M.25.40.cov.90)
# M.25.40.F.15.25
error.infer.clust.cov.100.men.25.40.F.15.25.cov.90 <- as.numeric(vector.MAR.true.cov.100.prop.men25.40.F.15.25) - as.numeric(vector.MAR.cov.90.cl.prop.men25.40.F.15.25)
RMSE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.90 <- RMSE(error.infer.clust.cov.100.men.25.40.F.15.25.cov.90)
MAE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.90 <- MAE(error.infer.clust.cov.100.men.25.40.F.15.25.cov.90)
ARMSE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.90 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men25.40.F.15.25, v2=vector.MAR.cov.90.cl.prop.men25.40.F.15.25)
MRE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.90 <- MRE(error.infer.clust.cov.100.men.25.40.F.15.25.cov.90)
# M.25.40.F.40.50
error.infer.clust.cov.100.men.25.40.F.40.50.cov.90 <- as.numeric(vector.MAR.true.cov.100.prop.men25.40.F.40.50) - as.numeric(vector.MAR.cov.90.cl.prop.men25.40.F.40.50)
RMSE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.90 <- RMSE(error.infer.clust.cov.100.men.25.40.F.40.50.cov.90)
MAE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.90 <- MAE(error.infer.clust.cov.100.men.25.40.F.40.50.cov.90)
ARMSE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.90 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men25.40.F.40.50, v2=vector.MAR.cov.90.cl.prop.men25.40.F.40.50)
MRE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.90 <- MRE(error.infer.clust.cov.100.men.25.40.F.40.50.cov.90)
# F.25.40.M.15.25
error.infer.clust.cov.100.women.25.40.M.15.25.cov.90 <- as.numeric(vector.MAR.true.cov.100.prop.women25.40.M.15.25) - as.numeric(vector.MAR.cov.90.cl.prop.women25.40.M.15.25)
RMSE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.90 <- RMSE(error.infer.clust.cov.100.women.25.40.M.15.25.cov.90)
MAE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.90 <- MAE(error.infer.clust.cov.100.women.25.40.M.15.25.cov.90)
ARMSE.error.infer.clust.cov.100.women.cov.90 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women25.40.M.15.25, v2=vector.MAR.cov.90.cl.prop.women25.40.M.15.25)
MRE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.90 <- MRE(error.infer.clust.cov.100.women.25.40.M.15.25.cov.90)
# F.25.40.M.40.50
error.infer.clust.cov.100.women.25.40.M.40.50.cov.90 <- as.numeric(vector.MAR.true.cov.100.prop.women25.40.M.40.50) - as.numeric(vector.MAR.cov.90.cl.prop.women25.40.M.40.50)
RMSE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.90 <- RMSE(error.infer.clust.cov.100.women.25.40.M.40.50.cov.90)
MAE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.90 <- MAE(error.infer.clust.cov.100.women.25.40.M.40.50.cov.90)
ARMSE.error.infer.clust.cov.100.women.cov.90 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women25.40.M.40.50, v2=vector.MAR.cov.90.cl.prop.women25.40.M.40.50)
MRE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.90 <- MRE(error.infer.clust.cov.100.women.25.40.M.40.50.cov.90)
# 40.50
# M.40.50.F.40.50
error.infer.clust.cov.100.men.40.50.F.40.50.cov.90 <- as.numeric(vector.MAR.true.cov.100.prop.men40.50.F.40.50) - as.numeric(vector.MAR.cov.90.cl.prop.men40.50.F.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.90 <- RMSE(error.infer.clust.cov.100.men.40.50.F.40.50.cov.90)
MAE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.90 <- MAE(error.infer.clust.cov.100.men.40.50.F.40.50.cov.90)
ARMSE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.90 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men40.50.F.40.50, v2=vector.MAR.cov.90.cl.prop.men40.50.F.40.50)
MRE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.90 <- MRE(error.infer.clust.cov.100.men.40.50.F.40.50.cov.90)
# F.40.50.M.40.50
error.infer.clust.cov.100.women.40.50.M.40.50.cov.90 <- as.numeric(vector.MAR.true.cov.100.prop.women40.50.M.40.50) - as.numeric(vector.MAR.cov.90.cl.prop.women40.50.M.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.90 <- RMSE(error.infer.clust.cov.100.women.40.50.M.40.50.cov.90)
MAE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.90 <- MAE(error.infer.clust.cov.100.women.40.50.M.40.50.cov.90)
ARMSE.error.infer.clust.cov.100.women.cov.90 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women40.50.M.40.50, v2=vector.MAR.cov.90.cl.prop.women40.50.M.40.50)
MRE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.90 <- MRE(error.infer.clust.cov.100.women.40.50.M.40.50.cov.90)
# M.40.50.F.15.25
error.infer.clust.cov.100.men.40.50.F.15.25.cov.90 <- as.numeric(vector.MAR.true.cov.100.prop.men40.50.F.15.25) - as.numeric(vector.MAR.cov.90.cl.prop.men40.50.F.15.25)
RMSE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.90 <- RMSE(error.infer.clust.cov.100.men.40.50.F.15.25.cov.90)
MAE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.90 <- MAE(error.infer.clust.cov.100.men.40.50.F.15.25.cov.90)
ARMSE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.90 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men40.50.F.15.25, v2=vector.MAR.cov.90.cl.prop.men40.50.F.15.25)
MRE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.90 <- MRE(error.infer.clust.cov.100.men.40.50.F.15.25.cov.90)
# M.40.50.F.25.40
error.infer.clust.cov.100.men.40.50.F.25.40.cov.90 <- as.numeric(vector.MAR.true.cov.100.prop.men40.50.F.25.40) - as.numeric(vector.MAR.cov.90.cl.prop.men40.50.F.25.40)
RMSE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.90 <- RMSE(error.infer.clust.cov.100.men.40.50.F.25.40.cov.90)
MAE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.90 <- MAE(error.infer.clust.cov.100.men.40.50.F.25.40.cov.90)
ARMSE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.90 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men40.50.F.25.40, v2=vector.MAR.cov.90.cl.prop.men40.50.F.25.40)
MRE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.90 <- MRE(error.infer.clust.cov.100.men.40.50.F.25.40.cov.90)
# F.40.50.M.15.25
error.infer.clust.cov.100.women.40.50.M.15.25.cov.90 <- as.numeric(vector.MAR.true.cov.100.prop.women40.50.M.15.25) - as.numeric(vector.MAR.cov.90.cl.prop.women40.50.M.15.25)
RMSE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.90 <- RMSE(error.infer.clust.cov.100.women.40.50.M.15.25.cov.90)
MAE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.90 <- MAE(error.infer.clust.cov.100.women.40.50.M.15.25.cov.90)
ARMSE.error.infer.clust.cov.100.women.cov.90 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women40.50.M.15.25, v2=vector.MAR.cov.90.cl.prop.women40.50.M.15.25)
MRE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.90 <- MRE(error.infer.clust.cov.100.women.40.50.M.15.25.cov.90)
# F.40.50.M.25.40
error.infer.clust.cov.100.women.40.50.M.25.40.cov.90 <- as.numeric(vector.MAR.true.cov.100.prop.women40.50.M.25.40) - as.numeric(vector.MAR.cov.90.cl.prop.women40.50.M.25.40)
RMSE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.90 <- RMSE(error.infer.clust.cov.100.women.40.50.M.25.40.cov.90)
MAE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.90 <- MAE(error.infer.clust.cov.100.women.40.50.M.25.40.cov.90)
ARMSE.error.infer.clust.cov.100.women.cov.90 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women40.50.M.25.40, v2=vector.MAR.cov.90.cl.prop.women40.50.M.25.40)
MRE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.90 <- MRE(error.infer.clust.cov.100.women.40.50.M.25.40.cov.90)
# Cov 95
# 15.25
# M.15.25.F.15.25
error.infer.clust.cov.100.men.15.25.F.15.25.cov.95 <- as.numeric(vector.MAR.true.cov.100.prop.men15.25.F.15.25) - as.numeric(vector.MAR.cov.95.cl.prop.men15.25.F.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.F.15.25.cov.95 <- RMSE(error.infer.clust.cov.100.men.15.25.F.15.25.cov.95)
MAE.error.infer.clust.cov.100.men.15.25cov.35 <- MAE(error.infer.clust.cov.100.men.15.25.F.15.25.cov.95)
ARMSE.error.infer.clust.cov.100.men.15.25cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men15.25.F.15.25, v2=vector.MAR.cov.95.cl.prop.men15.25.F.15.25)
MRE.error.infer.clust.cov.100.men.15.25.F.15.25.cov.95 <- MRE(error.infer.clust.cov.100.men.15.25.F.15.25.cov.95)
# F.15.25.M.15.25
error.infer.clust.cov.100.women.15.25.M.15.25.cov.95 <- as.numeric(vector.MAR.true.cov.100.prop.women15.25.M.15.25) - as.numeric(vector.MAR.cov.95.cl.prop.women15.25.M.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.95 <- RMSE(error.infer.clust.cov.100.women.15.25.M.15.25.cov.95)
MAE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.95 <- MAE(error.infer.clust.cov.100.women.15.25.M.15.25.cov.95)
ARMSE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.95 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women15.25.M.15.25, v2=vector.MAR.cov.95.cl.prop.women15.25.M.15.25)
MRE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.95 <- MRE(error.infer.clust.cov.100.women.15.25.M.15.25.cov.95)
# M.15.25.F.25.40
error.infer.clust.cov.100.men.15.25.F.25.40.cov.95 <- as.numeric(vector.MAR.true.cov.100.prop.men15.25.F.25.40) - as.numeric(vector.MAR.cov.95.cl.prop.men15.25.F.25.40)
RMSE.error.infer.clust.cov.100.men.15.25.F.25.40.cov.95 <- RMSE(error.infer.clust.cov.100.men.15.25.F.25.40.cov.95)
MAE.error.infer.clust.cov.100.men.15.25cov.35 <- MAE(error.infer.clust.cov.100.men.15.25.F.25.40.cov.95)
ARMSE.error.infer.clust.cov.100.men.15.25cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men15.25.F.25.40, v2=vector.MAR.cov.95.cl.prop.men15.25.F.25.40)
MRE.error.infer.clust.cov.100.men.15.25.F.25.40.cov.95 <- MRE(error.infer.clust.cov.100.men.15.25.F.25.40.cov.95)
# M.15.25.F.40.50
error.infer.clust.cov.100.men.15.25.F.40.50.cov.95 <- as.numeric(vector.MAR.true.cov.100.prop.men15.25.F.40.50) - as.numeric(vector.MAR.cov.95.cl.prop.men15.25.F.40.50)
RMSE.error.infer.clust.cov.100.men.15.25.F.40.50.cov.95 <- RMSE(error.infer.clust.cov.100.men.15.25.F.40.50.cov.95)
MAE.error.infer.clust.cov.100.men.15.25cov.35 <- MAE(error.infer.clust.cov.100.men.15.25.F.40.50.cov.95)
ARMSE.error.infer.clust.cov.100.men.15.25cov.35 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men15.25.F.40.50, v2=vector.MAR.cov.95.cl.prop.men15.25.F.40.50)
MRE.error.infer.clust.cov.100.men.15.25.F.40.50.cov.95 <- MRE(error.infer.clust.cov.100.men.15.25.F.40.50.cov.95)
# F.15.25.M.25.40
error.infer.clust.cov.100.women.15.25.M.25.40.cov.95 <- as.numeric(vector.MAR.true.cov.100.prop.women15.25.M.25.40) - as.numeric(vector.MAR.cov.95.cl.prop.women15.25.M.25.40)
RMSE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.95 <- RMSE(error.infer.clust.cov.100.women.15.25.M.25.40.cov.95)
MAE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.95 <- MAE(error.infer.clust.cov.100.women.15.25.M.25.40.cov.95)
ARMSE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.95 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women15.25.M.25.40, v2=vector.MAR.cov.95.cl.prop.women15.25.M.25.40)
MRE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.95 <- MRE(error.infer.clust.cov.100.women.15.25.M.25.40.cov.95)
# F.15.25.M.40.50
error.infer.clust.cov.100.women.15.25.M.40.50.cov.95 <- as.numeric(vector.MAR.true.cov.100.prop.women15.25.M.40.50) - as.numeric(vector.MAR.cov.95.cl.prop.women15.25.M.40.50)
RMSE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.95 <- RMSE(error.infer.clust.cov.100.women.15.25.M.40.50.cov.95)
MAE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.95 <- MAE(error.infer.clust.cov.100.women.15.25.M.40.50.cov.95)
ARMSE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.95 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women15.25.M.40.50, v2=vector.MAR.cov.95.cl.prop.women15.25.M.40.50)
MRE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.95 <- MRE(error.infer.clust.cov.100.women.15.25.M.40.50.cov.95)
# 25.40
# M.25.40.F.25.40
error.infer.clust.cov.100.men.25.40.F.25.40.cov.95 <- as.numeric(vector.MAR.true.cov.100.prop.men25.40.F.25.40) - as.numeric(vector.MAR.cov.95.cl.prop.men25.40.F.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.95 <- RMSE(error.infer.clust.cov.100.men.25.40.F.25.40.cov.95)
MAE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.95 <- MAE(error.infer.clust.cov.100.men.25.40.F.25.40.cov.95)
ARMSE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.95 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men25.40.F.25.40, v2=vector.MAR.cov.95.cl.prop.men25.40.F.25.40)
MRE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.95 <- MRE(error.infer.clust.cov.100.men.25.40.F.25.40.cov.95)
# F.25.40.M.25.40
error.infer.clust.cov.100.women.25.40.M.25.40.cov.95 <- as.numeric(vector.MAR.true.cov.100.prop.women25.40.M.25.40) - as.numeric(vector.MAR.cov.95.cl.prop.women25.40.M.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.95 <- RMSE(error.infer.clust.cov.100.women.25.40.M.25.40.cov.95)
MAE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.95 <- MAE(error.infer.clust.cov.100.women.25.40.M.25.40.cov.95)
ARMSE.error.infer.clust.cov.100.women.cov.95 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women25.40.M.25.40, v2=vector.MAR.cov.95.cl.prop.women25.40.M.25.40)
MRE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.95 <- MRE(error.infer.clust.cov.100.women.25.40.M.25.40.cov.95)
# M.25.40.F.15.25
error.infer.clust.cov.100.men.25.40.F.15.25.cov.95 <- as.numeric(vector.MAR.true.cov.100.prop.men25.40.F.15.25) - as.numeric(vector.MAR.cov.95.cl.prop.men25.40.F.15.25)
RMSE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.95 <- RMSE(error.infer.clust.cov.100.men.25.40.F.15.25.cov.95)
MAE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.95 <- MAE(error.infer.clust.cov.100.men.25.40.F.15.25.cov.95)
ARMSE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.95 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men25.40.F.15.25, v2=vector.MAR.cov.95.cl.prop.men25.40.F.15.25)
MRE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.95 <- MRE(error.infer.clust.cov.100.men.25.40.F.15.25.cov.95)
# M.25.40.F.40.50
error.infer.clust.cov.100.men.25.40.F.40.50.cov.95 <- as.numeric(vector.MAR.true.cov.100.prop.men25.40.F.40.50) - as.numeric(vector.MAR.cov.95.cl.prop.men25.40.F.40.50)
RMSE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.95 <- RMSE(error.infer.clust.cov.100.men.25.40.F.40.50.cov.95)
MAE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.95 <- MAE(error.infer.clust.cov.100.men.25.40.F.40.50.cov.95)
ARMSE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.95 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men25.40.F.40.50, v2=vector.MAR.cov.95.cl.prop.men25.40.F.40.50)
MRE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.95 <- MRE(error.infer.clust.cov.100.men.25.40.F.40.50.cov.95)
# F.25.40.M.15.25
error.infer.clust.cov.100.women.25.40.M.15.25.cov.95 <- as.numeric(vector.MAR.true.cov.100.prop.women25.40.M.15.25) - as.numeric(vector.MAR.cov.95.cl.prop.women25.40.M.15.25)
RMSE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.95 <- RMSE(error.infer.clust.cov.100.women.25.40.M.15.25.cov.95)
MAE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.95 <- MAE(error.infer.clust.cov.100.women.25.40.M.15.25.cov.95)
ARMSE.error.infer.clust.cov.100.women.cov.95 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women25.40.M.15.25, v2=vector.MAR.cov.95.cl.prop.women25.40.M.15.25)
MRE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.95 <- MRE(error.infer.clust.cov.100.women.25.40.M.15.25.cov.95)
# F.25.40.M.40.50
error.infer.clust.cov.100.women.25.40.M.40.50.cov.95 <- as.numeric(vector.MAR.true.cov.100.prop.women25.40.M.40.50) - as.numeric(vector.MAR.cov.95.cl.prop.women25.40.M.40.50)
RMSE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.95 <- RMSE(error.infer.clust.cov.100.women.25.40.M.40.50.cov.95)
MAE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.95 <- MAE(error.infer.clust.cov.100.women.25.40.M.40.50.cov.95)
ARMSE.error.infer.clust.cov.100.women.cov.95 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women25.40.M.40.50, v2=vector.MAR.cov.95.cl.prop.women25.40.M.40.50)
MRE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.95 <- MRE(error.infer.clust.cov.100.women.25.40.M.40.50.cov.95)
# 40.50
# M.40.50.F.40.50
error.infer.clust.cov.100.men.40.50.F.40.50.cov.95 <- as.numeric(vector.MAR.true.cov.100.prop.men40.50.F.40.50) - as.numeric(vector.MAR.cov.95.cl.prop.men40.50.F.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.95 <- RMSE(error.infer.clust.cov.100.men.40.50.F.40.50.cov.95)
MAE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.95 <- MAE(error.infer.clust.cov.100.men.40.50.F.40.50.cov.95)
ARMSE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.95 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men40.50.F.40.50, v2=vector.MAR.cov.95.cl.prop.men40.50.F.40.50)
MRE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.95 <- MRE(error.infer.clust.cov.100.men.40.50.F.40.50.cov.95)
# F.40.50.M.40.50
error.infer.clust.cov.100.women.40.50.M.40.50.cov.95 <- as.numeric(vector.MAR.true.cov.100.prop.women40.50.M.40.50) - as.numeric(vector.MAR.cov.95.cl.prop.women40.50.M.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.95 <- RMSE(error.infer.clust.cov.100.women.40.50.M.40.50.cov.95)
MAE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.95 <- MAE(error.infer.clust.cov.100.women.40.50.M.40.50.cov.95)
ARMSE.error.infer.clust.cov.100.women.cov.95 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women40.50.M.40.50, v2=vector.MAR.cov.95.cl.prop.women40.50.M.40.50)
MRE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.95 <- MRE(error.infer.clust.cov.100.women.40.50.M.40.50.cov.95)
# M.40.50.F.15.25
error.infer.clust.cov.100.men.40.50.F.15.25.cov.95 <- as.numeric(vector.MAR.true.cov.100.prop.men40.50.F.15.25) - as.numeric(vector.MAR.cov.95.cl.prop.men40.50.F.15.25)
RMSE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.95 <- RMSE(error.infer.clust.cov.100.men.40.50.F.15.25.cov.95)
MAE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.95 <- MAE(error.infer.clust.cov.100.men.40.50.F.15.25.cov.95)
ARMSE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.95 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men40.50.F.15.25, v2=vector.MAR.cov.95.cl.prop.men40.50.F.15.25)
MRE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.95 <- MRE(error.infer.clust.cov.100.men.40.50.F.15.25.cov.95)
# M.40.50.F.25.40
error.infer.clust.cov.100.men.40.50.F.25.40.cov.95 <- as.numeric(vector.MAR.true.cov.100.prop.men40.50.F.25.40) - as.numeric(vector.MAR.cov.95.cl.prop.men40.50.F.25.40)
RMSE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.95 <- RMSE(error.infer.clust.cov.100.men.40.50.F.25.40.cov.95)
MAE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.95 <- MAE(error.infer.clust.cov.100.men.40.50.F.25.40.cov.95)
ARMSE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.95 <- ARMSE(v1=vector.MAR.true.cov.100.prop.men40.50.F.25.40, v2=vector.MAR.cov.95.cl.prop.men40.50.F.25.40)
MRE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.95 <- MRE(error.infer.clust.cov.100.men.40.50.F.25.40.cov.95)
# F.40.50.M.15.25
error.infer.clust.cov.100.women.40.50.M.15.25.cov.95 <- as.numeric(vector.MAR.true.cov.100.prop.women40.50.M.15.25) - as.numeric(vector.MAR.cov.95.cl.prop.women40.50.M.15.25)
RMSE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.95 <- RMSE(error.infer.clust.cov.100.women.40.50.M.15.25.cov.95)
MAE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.95 <- MAE(error.infer.clust.cov.100.women.40.50.M.15.25.cov.95)
ARMSE.error.infer.clust.cov.100.women.cov.95 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women40.50.M.15.25, v2=vector.MAR.cov.95.cl.prop.women40.50.M.15.25)
MRE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.95 <- MRE(error.infer.clust.cov.100.women.40.50.M.15.25.cov.95)
# F.40.50.M.25.40
error.infer.clust.cov.100.women.40.50.M.25.40.cov.95 <- as.numeric(vector.MAR.true.cov.100.prop.women40.50.M.25.40) - as.numeric(vector.MAR.cov.95.cl.prop.women40.50.M.25.40)
RMSE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.95 <- RMSE(error.infer.clust.cov.100.women.40.50.M.25.40.cov.95)
MAE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.95 <- MAE(error.infer.clust.cov.100.women.40.50.M.25.40.cov.95)
ARMSE.error.infer.clust.cov.100.women.cov.95 <- ARMSE(v1=vector.MAR.true.cov.100.prop.women40.50.M.25.40, v2=vector.MAR.cov.95.cl.prop.women40.50.M.25.40)
MRE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.95 <- MRE(error.infer.clust.cov.100.women.40.50.M.25.40.cov.95)# Figures -----------------
RMSE.error.infer.clust.cov.100.prop.men.15.25.F.15.25 <- data.frame(x=c("35", "40", "45", "50", "55", "60",
"65", "70", "75", "80", "85", "90", "95"),
F = c(RMSE.error.infer.clust.cov.100.men.15.25.F.15.25.cov.35, RMSE.error.infer.clust.cov.100.men.15.25.F.15.25.cov.40,
RMSE.error.infer.clust.cov.100.men.15.25.F.15.25.cov.45, RMSE.error.infer.clust.cov.100.men.15.25.F.15.25.cov.50,
RMSE.error.infer.clust.cov.100.men.15.25.F.15.25.cov.55, RMSE.error.infer.clust.cov.100.men.15.25.F.15.25.cov.60,
RMSE.error.infer.clust.cov.100.men.15.25.F.15.25.cov.65, RMSE.error.infer.clust.cov.100.men.15.25.F.15.25.cov.70,
RMSE.error.infer.clust.cov.100.men.15.25.F.15.25.cov.75, RMSE.error.infer.clust.cov.100.men.15.25.F.15.25.cov.80,
RMSE.error.infer.clust.cov.100.men.15.25.F.15.25.cov.85, RMSE.error.infer.clust.cov.100.men.15.25.F.15.25.cov.90,
RMSE.error.infer.clust.cov.100.men.15.25.F.15.25.cov.95))
RMSE.error.infer.clust.cov.100.prop.men.15.25.F.15.25$param <- rep("M.15.25.F.15.25", nrow(RMSE.error.infer.clust.cov.100.prop.men.15.25.F.15.25))
plot.RMSE.error.infer.clust.cov.100.prop.men.15.25.F.15.25 <- ggplot(RMSE.error.infer.clust.cov.100.prop.men.15.25.F.15.25, aes(x = x, y = F)) +
geom_point(size = 4) +
ggtitle("Proportion for men 15 - 25 with women 15 - 25 - MCAR") +
xlab("Sequence sampling coverage") + ylab("Error value")
# plot.RMSE.error.infer.clust.cov.100.prop.men.15.25.F.15.25RMSE.error.infer.clust.cov.100.prop.men.15.25.F.25.40 <- data.frame(x=c("35", "40", "45", "50", "55", "60", "65", "70", "75", "80", "85", "90", "95"),
F = c(RMSE.error.infer.clust.cov.100.men.15.25.F.25.40.cov.35, RMSE.error.infer.clust.cov.100.men.15.25.F.25.40.cov.40,
RMSE.error.infer.clust.cov.100.men.15.25.F.25.40.cov.45, RMSE.error.infer.clust.cov.100.men.15.25.F.25.40.cov.50,
RMSE.error.infer.clust.cov.100.men.15.25.F.25.40.cov.55, RMSE.error.infer.clust.cov.100.men.15.25.F.25.40.cov.60,
RMSE.error.infer.clust.cov.100.men.15.25.F.25.40.cov.65, RMSE.error.infer.clust.cov.100.men.15.25.F.25.40.cov.70,
RMSE.error.infer.clust.cov.100.men.15.25.F.25.40.cov.75, RMSE.error.infer.clust.cov.100.men.15.25.F.25.40.cov.80,
RMSE.error.infer.clust.cov.100.men.15.25.F.25.40.cov.85, RMSE.error.infer.clust.cov.100.men.15.25.F.25.40.cov.90,
RMSE.error.infer.clust.cov.100.men.15.25.F.25.40.cov.95))
RMSE.error.infer.clust.cov.100.prop.men.15.25.F.25.40$param <- rep("M.15.25.F.25.40", nrow(RMSE.error.infer.clust.cov.100.prop.men.15.25.F.25.40))
plot.RMSE.error.infer.clust.cov.100.prop.men.15.25.F.25.40 <- ggplot(RMSE.error.infer.clust.cov.100.prop.men.15.25.F.25.40, aes(x = x, y = F)) +
geom_point(size = 4) +
ggtitle("Proportion for men 15 - 25 and women 25 - 40 - MCAR") +
xlab("Sequence sampling coverage") + ylab("Error value")
# plot.RMSE.error.infer.clust.cov.100.prop.men.15.25.F.25.40RMSE.error.infer.clust.cov.100.prop.men.15.25.F.40.50 <- data.frame(x=c("35", "40", "45", "50", "55", "60", "65", "70", "75", "80", "85", "90", "95"),
F = c(RMSE.error.infer.clust.cov.100.men.15.25.F.40.50.cov.35, RMSE.error.infer.clust.cov.100.men.15.25.F.40.50.cov.40,
RMSE.error.infer.clust.cov.100.men.15.25.F.40.50.cov.45, RMSE.error.infer.clust.cov.100.men.15.25.F.40.50.cov.50,
RMSE.error.infer.clust.cov.100.men.15.25.F.40.50.cov.55, RMSE.error.infer.clust.cov.100.men.15.25.F.40.50.cov.60,
RMSE.error.infer.clust.cov.100.men.15.25.F.40.50.cov.65, RMSE.error.infer.clust.cov.100.men.15.25.F.40.50.cov.70,
RMSE.error.infer.clust.cov.100.men.15.25.F.40.50.cov.75, RMSE.error.infer.clust.cov.100.men.15.25.F.40.50.cov.80,
RMSE.error.infer.clust.cov.100.men.15.25.F.40.50.cov.85, RMSE.error.infer.clust.cov.100.men.15.25.F.40.50.cov.90,
RMSE.error.infer.clust.cov.100.men.15.25.F.40.50.cov.95))
RMSE.error.infer.clust.cov.100.prop.men.15.25.F.40.50$param <- rep("M.15.25.F.40.50", nrow(RMSE.error.infer.clust.cov.100.prop.men.15.25.F.40.50))
plot.RMSE.error.infer.clust.cov.100.prop.men.15.25.F.40.50 <- ggplot(RMSE.error.infer.clust.cov.100.prop.men.15.25.F.40.50, aes(x = x, y = F)) +
geom_point(size = 4) +
ggtitle("Proportion for men 15 - 25 with women 40 - 50 - MCAR") +
xlab("Sequence sampling coverage") + ylab("Error value")
# plot.RMSE.error.infer.clust.cov.100.prop.men.15.25.F.40.50RMSE.error.infer.clust.cov.100.prop.women.15.25.M.15.25 <- data.frame(x=c("35", "40", "45", "50", "55", "60", "65", "70", "75", "80", "85", "90", "95"),
F = c(RMSE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.35, RMSE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.40,
RMSE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.45, RMSE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.50,
RMSE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.55, RMSE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.60,
RMSE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.65, RMSE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.70,
RMSE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.75, RMSE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.80,
RMSE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.85, RMSE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.90,
RMSE.error.infer.clust.cov.100.women.15.25.M.15.25.cov.95))
RMSE.error.infer.clust.cov.100.prop.women.15.25.M.15.25$param <- rep("F.15.25.M.15.25", nrow(RMSE.error.infer.clust.cov.100.prop.women.15.25.M.15.25))
plot.RMSE.error.infer.clust.cov.100.prop.women.15.25.M.15.25 <- ggplot(RMSE.error.infer.clust.cov.100.prop.women.15.25.M.15.25, aes(x = x, y = F)) +
geom_point(size = 4) +
ggtitle("Proportion for women 15 - 25 with men in 15 - 25 - MCAR") +
xlab("Sequence sampling coverage") + ylab("Error value")
# plot.RMSE.error.infer.clust.cov.100.prop.women.15.25.M.15.25RMSE.error.infer.clust.cov.100.prop.women.15.25.M.25.40 <- data.frame(x=c("35", "40", "45", "50", "55", "60", "65", "70", "75", "80", "85", "90", "95"),
F = c(RMSE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.35, RMSE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.40,
RMSE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.45, RMSE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.50,
RMSE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.55, RMSE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.60,
RMSE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.65, RMSE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.70,
RMSE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.75, RMSE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.80,
RMSE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.85, RMSE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.90,
RMSE.error.infer.clust.cov.100.women.15.25.M.25.40.cov.95))
RMSE.error.infer.clust.cov.100.prop.women.15.25.M.25.40$param <- rep("F.15.25.M.25.40", nrow(RMSE.error.infer.clust.cov.100.prop.women.15.25.M.25.40))
plot.RMSE.error.infer.clust.cov.100.prop.women.15.25.M.25.40 <- ggplot(RMSE.error.infer.clust.cov.100.prop.women.15.25.M.25.40, aes(x = x, y = F)) +
geom_point(size = 4) +
ggtitle("Proportion for women 15 - 25 with men 25 - 40 - MCAR") +
xlab("Sequence sampling coverage") + ylab("Error value")
# plot.RMSE.error.infer.clust.cov.100.prop.women.15.25.M.25.40RMSE.error.infer.clust.cov.100.prop.women.15.25.M.40.50 <- data.frame(x=c("35", "40", "45", "50", "55", "60", "65", "70", "75", "80", "85", "90", "95"),
F = c(RMSE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.35, RMSE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.40,
RMSE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.45, RMSE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.50,
RMSE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.55, RMSE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.60,
RMSE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.65, RMSE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.70,
RMSE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.75, RMSE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.80,
RMSE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.85, RMSE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.90,
RMSE.error.infer.clust.cov.100.women.15.25.M.40.50.cov.95))
RMSE.error.infer.clust.cov.100.prop.women.15.25.M.40.50$param <- rep("F.15.25.M.40.50", nrow(RMSE.error.infer.clust.cov.100.prop.women.15.25.M.40.50))
plot.RMSE.error.infer.clust.cov.100.prop.women.15.25.M.40.50 <- ggplot(RMSE.error.infer.clust.cov.100.prop.women.15.25.M.40.50, aes(x = x, y = F)) +
geom_point(size = 4) +
ggtitle("Proportion for women 15 - 25 with men 40 - 50 - MCAR") +
xlab("Sequence sampling coverage") + ylab("Error value")
# plot.RMSE.error.infer.clust.cov.100.prop.women.15.25.M.40.50RMSE.error.infer.clust.cov.100.prop.men.25.40.F.25.40 <- data.frame(x=c("35", "40", "45", "50", "55", "60", "65", "70", "75", "80", "85", "90", "95"),
F = c(RMSE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.35, RMSE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.40,
RMSE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.45, RMSE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.50,
RMSE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.55, RMSE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.60,
RMSE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.65, RMSE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.70,
RMSE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.75, RMSE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.80,
RMSE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.85, RMSE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.90,
RMSE.error.infer.clust.cov.100.men.25.40.F.25.40.cov.95))
RMSE.error.infer.clust.cov.100.prop.men.25.40.F.25.40$param <- rep("M.25.40.F.25.40", nrow(RMSE.error.infer.clust.cov.100.prop.men.25.40.F.25.40))
plot.RMSE.error.infer.clust.cov.100.prop.men.25.40.F.25.40 <- ggplot(RMSE.error.infer.clust.cov.100.prop.men.25.40.F.25.40, aes(x = x, y = F)) +
geom_point(size = 4) +
ggtitle("Proportion for men 25 - 40 with women in 25 - 40 - MCAR") +
xlab("Sequence sampling coverage") + ylab("Error value")
# plot.RMSE.error.infer.clust.cov.100.prop.men.25.40.F.25.40RMSE.error.infer.clust.cov.100.prop.men.25.40.F.15.25 <- data.frame(x=c("35", "40", "45", "50", "55", "60", "65", "70", "75", "80", "85", "90", "95"),
F = c(RMSE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.35, RMSE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.40,
RMSE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.45, RMSE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.50,
RMSE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.55, RMSE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.60,
RMSE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.65, RMSE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.70,
RMSE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.75, RMSE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.80,
RMSE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.85, RMSE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.90,
RMSE.error.infer.clust.cov.100.men.25.40.F.15.25.cov.95))
RMSE.error.infer.clust.cov.100.prop.men.25.40.F.15.25$param <- rep("M.25.40.F.15.25", nrow(RMSE.error.infer.clust.cov.100.prop.men.25.40.F.15.25))
plot.RMSE.error.infer.clust.cov.100.prop.men.25.40.F.15.25 <- ggplot(RMSE.error.infer.clust.cov.100.prop.men.25.40.F.15.25, aes(x = x, y = F)) +
geom_point(size = 4) +
ggtitle("Proportion for men 25 - 40 with women 15 - 25 - MCAR") +
xlab("Sequence sampling coverage") + ylab("Error value")
# plot.RMSE.error.infer.clust.cov.100.prop.men.25.40.F.15.25RMSE.error.infer.clust.cov.100.prop.men.25.40.F.40.50 <- data.frame(x=c("35", "40", "45", "50", "55", "60", "65", "70", "75", "80", "85", "90", "95"),
F = c(RMSE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.35, RMSE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.40,
RMSE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.45, RMSE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.50,
RMSE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.55, RMSE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.60,
RMSE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.65, RMSE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.70,
RMSE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.75, RMSE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.80,
RMSE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.85, RMSE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.90,
RMSE.error.infer.clust.cov.100.men.25.40.F.40.50.cov.95))
RMSE.error.infer.clust.cov.100.prop.men.25.40.F.40.50$param <- rep("M.25.40.F.40.50", nrow(RMSE.error.infer.clust.cov.100.prop.men.25.40.F.40.50))
plot.RMSE.error.infer.clust.cov.100.prop.men.25.40.F.40.50 <- ggplot(RMSE.error.infer.clust.cov.100.prop.men.25.40.F.40.50, aes(x = x, y = F)) +
geom_point(size = 4) +
ggtitle("Proportion for men 25 - 40 with women 40 - 50 - MCAR") +
xlab("Sequence sampling coverage") + ylab("Error value")
# plot.RMSE.error.infer.clust.cov.100.prop.men.25.40.F.40.50RMSE.error.infer.clust.cov.100.prop.women.25.40.M.25.40 <- data.frame(x=c("35", "40", "45", "50", "55", "60", "65", "70", "75", "80", "85", "90", "95"),
F = c(RMSE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.35, RMSE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.40,
RMSE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.45, RMSE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.50,
RMSE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.55, RMSE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.60,
RMSE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.65, RMSE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.70,
RMSE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.75, RMSE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.80,
RMSE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.85, RMSE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.90,
RMSE.error.infer.clust.cov.100.women.25.40.M.25.40.cov.95))
RMSE.error.infer.clust.cov.100.prop.women.25.40.M.25.40$param <- rep("F.25.40.M.25.40", nrow(RMSE.error.infer.clust.cov.100.prop.women.25.40.M.25.40))
plot.RMSE.error.infer.clust.cov.100.prop.women.25.40.M.25.40 <- ggplot(RMSE.error.infer.clust.cov.100.prop.women.25.40.M.25.40, aes(x = x, y = F)) +
geom_point(size = 4) +
ggtitle("Proportion for women 25 - 40 with men in 25 - 40 - MCAR") +
xlab("Sequence sampling coverage") + ylab("Error value")
# plot.RMSE.error.infer.clust.cov.100.prop.women.25.40.M.25.40RMSE.error.infer.clust.cov.100.prop.women.25.40.M.15.25 <- data.frame(x=c("35", "40", "45", "50", "55", "60", "65", "70", "75", "80", "85", "90", "95"),
F = c(RMSE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.35, RMSE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.40,
RMSE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.45, RMSE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.50,
RMSE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.55, RMSE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.60,
RMSE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.65, RMSE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.70,
RMSE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.75, RMSE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.80,
RMSE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.85, RMSE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.90,
RMSE.error.infer.clust.cov.100.women.25.40.M.15.25.cov.95))
RMSE.error.infer.clust.cov.100.prop.women.25.40.M.15.25$param <- rep("F.25.40.M.15.25", nrow(RMSE.error.infer.clust.cov.100.prop.women.25.40.M.15.25))
plot.RMSE.error.infer.clust.cov.100.prop.women.25.40.M.15.25 <- ggplot(RMSE.error.infer.clust.cov.100.prop.women.25.40.M.15.25, aes(x = x, y = F)) +
geom_point(size = 4) +
ggtitle("Proportion for women 25 - 40 with men 15 - 25 - MCAR") +
xlab("Sequence sampling coverage") + ylab("Error value")
# plot.RMSE.error.infer.clust.cov.100.prop.women.25.40.M.15.25RMSE.error.infer.clust.cov.100.prop.women.25.40.M.40.50 <- data.frame(x=c("35", "40", "45", "50", "55", "60", "65", "70", "75", "80", "85", "90", "95"),
F = c(RMSE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.35, RMSE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.40,
RMSE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.45, RMSE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.50,
RMSE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.55, RMSE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.60,
RMSE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.65, RMSE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.70,
RMSE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.75, RMSE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.80,
RMSE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.85, RMSE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.90,
RMSE.error.infer.clust.cov.100.women.25.40.M.40.50.cov.95))
RMSE.error.infer.clust.cov.100.prop.women.25.40.M.40.50$param <- rep("F.25.40.M.40.50", nrow(RMSE.error.infer.clust.cov.100.prop.women.25.40.M.40.50))
plot.RMSE.error.infer.clust.cov.100.prop.women.25.40.M.40.50 <- ggplot(RMSE.error.infer.clust.cov.100.prop.women.25.40.M.40.50, aes(x = x, y = F)) +
geom_point(size = 4) +
ggtitle("Proportion for women 25 - 40 with men 40 - 50 - MCAR") +
xlab("Sequence sampling coverage") + ylab("Error value")
# plot.RMSE.error.infer.clust.cov.100.prop.women.25.40.M.40.50RMSE.error.infer.clust.cov.100.prop.men.40.50.F.40.50 <- data.frame(x=c("35", "40", "45", "50", "55", "60", "65", "70", "75", "80", "85", "90", "95"),
F = c(RMSE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.35, RMSE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.40,
RMSE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.45, RMSE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.50,
RMSE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.55, RMSE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.60,
RMSE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.65, RMSE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.70,
RMSE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.75, RMSE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.80,
RMSE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.85, RMSE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.90,
RMSE.error.infer.clust.cov.100.men.40.50.F.40.50.cov.95))
RMSE.error.infer.clust.cov.100.prop.men.40.50.F.40.50$param <- rep("M.40.50.F.40.50", nrow(RMSE.error.infer.clust.cov.100.prop.men.40.50.F.40.50))
plot.RMSE.error.infer.clust.cov.100.prop.men.40.50.F.40.50 <- ggplot(RMSE.error.infer.clust.cov.100.prop.men.40.50.F.40.50, aes(x = x, y = F)) +
geom_point(size = 4) +
ggtitle("Proportion for men 40 - 50 with women in 40 - 50 - MCAR") +
xlab("Sequence sampling coverage") + ylab("Error value")
# plot.RMSE.error.infer.clust.cov.100.prop.men.40.50.F.40.50RMSE.error.infer.clust.cov.100.prop.men.40.50.F.15.25 <- data.frame(x=c("35", "40", "45", "50", "55", "60", "65", "70", "75", "80", "85", "90", "95"),
F = c(RMSE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.35, RMSE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.40,
RMSE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.45, RMSE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.50,
RMSE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.55, RMSE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.60,
RMSE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.65, RMSE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.70,
RMSE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.75, RMSE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.80,
RMSE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.85, RMSE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.90,
RMSE.error.infer.clust.cov.100.men.40.50.F.15.25.cov.95))
RMSE.error.infer.clust.cov.100.prop.men.40.50.F.15.25$param <- rep("M.40.50.F.15.25", nrow(RMSE.error.infer.clust.cov.100.prop.men.40.50.F.15.25))
plot.RMSE.error.infer.clust.cov.100.prop.men.40.50.F.15.25 <- ggplot(RMSE.error.infer.clust.cov.100.prop.men.40.50.F.15.25, aes(x = x, y = F)) +
geom_point(size = 4) +
ggtitle("Proportion for men 40 - 50 with women 15 - 25 - MCAR") +
xlab("Sequence sampling coverage") + ylab("Error value")
# plot.RMSE.error.infer.clust.cov.100.prop.men.40.50.F.15.25RMSE.error.infer.clust.cov.100.prop.men.40.50.F.25.40 <- data.frame(x=c("35", "40", "45", "50", "55", "60", "65", "70", "75", "80", "85", "90", "95"),
F = c(RMSE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.35, RMSE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.40,
RMSE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.45, RMSE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.50,
RMSE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.55, RMSE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.60,
RMSE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.65, RMSE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.70,
RMSE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.75, RMSE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.80,
RMSE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.85, RMSE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.90,
RMSE.error.infer.clust.cov.100.men.40.50.F.25.40.cov.95))
RMSE.error.infer.clust.cov.100.prop.men.40.50.F.25.40$param <- rep("M.40.50.F.25.40", nrow(RMSE.error.infer.clust.cov.100.prop.men.40.50.F.25.40))
plot.RMSE.error.infer.clust.cov.100.prop.men.40.50.F.25.40 <- ggplot(RMSE.error.infer.clust.cov.100.prop.men.40.50.F.25.40, aes(x = x, y = F)) +
geom_point(size = 4) +
ggtitle("Proportion for men 40 - 50 with women 25 - 40 - MCAR") +
xlab("Sequence sampling coverage") + ylab("Error value")
# plot.RMSE.error.infer.clust.cov.100.prop.men.40.50.F.25.40RMSE.error.infer.clust.cov.100.prop.women.40.50.M.40.50 <- data.frame(x=c("35", "40", "45", "50", "55", "60", "65", "70", "75", "80", "85", "90", "95"),
F = c(RMSE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.35, RMSE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.40,
RMSE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.45, RMSE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.50,
RMSE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.55, RMSE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.60,
RMSE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.65, RMSE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.70,
RMSE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.75, RMSE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.80,
RMSE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.85, RMSE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.90,
RMSE.error.infer.clust.cov.100.women.40.50.M.40.50.cov.95))
RMSE.error.infer.clust.cov.100.prop.women.40.50.M.40.50$param <- rep("F.40.50.M.40.50", nrow(RMSE.error.infer.clust.cov.100.prop.women.40.50.M.40.50))
plot.RMSE.error.infer.clust.cov.100.prop.women.40.50.M.40.50 <- ggplot(RMSE.error.infer.clust.cov.100.prop.women.40.50.M.40.50, aes(x = x, y = F)) +
geom_point(size = 4) +
ggtitle("Proportion for women 40 - 50 with men in 40 - 50 - MCAR") +
xlab("Sequence sampling coverage") + ylab("Error value")
# plot.RMSE.error.infer.clust.cov.100.prop.women.40.50.M.40.50RMSE.error.infer.clust.cov.100.prop.women.40.50.M.15.25 <- data.frame(x=c("35", "40", "45", "50", "55", "60", "65", "70", "75", "80", "85", "90", "95"),
F = c(RMSE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.35, RMSE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.40,
RMSE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.45, RMSE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.50,
RMSE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.55, RMSE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.60,
RMSE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.65, RMSE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.70,
RMSE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.75, RMSE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.80,
RMSE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.85, RMSE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.90,
RMSE.error.infer.clust.cov.100.women.40.50.M.15.25.cov.95))
RMSE.error.infer.clust.cov.100.prop.women.40.50.M.15.25$param <- rep("F.40.50.M.15.25", nrow(RMSE.error.infer.clust.cov.100.prop.women.40.50.M.15.25))
plot.RMSE.error.infer.clust.cov.100.prop.women.40.50.M.15.25 <- ggplot(RMSE.error.infer.clust.cov.100.prop.women.40.50.M.15.25, aes(x = x, y = F)) +
geom_point(size = 4) +
ggtitle("Proportion for women 40 - 50 with men 15 - 25 - MCAR") +
xlab("Sequence sampling coverage") + ylab("Error value")
# plot.RMSE.error.infer.clust.cov.100.prop.women.40.50.M.15.25RMSE.error.infer.clust.cov.100.prop.women.40.50.M.25.40 <- data.frame(x=c("35", "40", "45", "50", "55", "60", "65", "70", "75", "80", "85", "90", "95"),
F = c(RMSE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.35, RMSE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.40,
RMSE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.45, RMSE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.50,
RMSE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.55, RMSE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.60,
RMSE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.65, RMSE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.70,
RMSE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.75, RMSE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.80,
RMSE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.85, RMSE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.90,
RMSE.error.infer.clust.cov.100.women.40.50.M.25.40.cov.95))
RMSE.error.infer.clust.cov.100.prop.women.40.50.M.25.40$param <- rep("F.40.50.M.25.40", nrow(RMSE.error.infer.clust.cov.100.prop.women.40.50.M.25.40))
plot.RMSE.error.infer.clust.cov.100.prop.women.40.50.M.25.40 <- ggplot(RMSE.error.infer.clust.cov.100.prop.women.40.50.M.25.40, aes(x = x, y = F)) +
geom_point(size = 4) +
ggtitle("Proportion for women 40 - 50 with men 25 - 40 - MCAR") +
xlab("Sequence sampling coverage") + ylab("Error value")
# plot.RMSE.error.infer.clust.cov.100.prop.women.40.50.M.25.404.3.1 Goodness of fit of proportions of pairings for critical age groups
df_gps <- rbind(
# RMSE.error.infer.clust.cov.100.prop.women.40.50.M.25.40,
# RMSE.error.infer.clust.cov.100.prop.women.40.50.M.15.25,
# RMSE.error.infer.clust.cov.100.prop.women.40.50.M.40.50,
RMSE.error.infer.clust.cov.100.prop.men.40.50.F.25.40,
RMSE.error.infer.clust.cov.100.prop.men.40.50.F.15.25,
# RMSE.error.infer.clust.cov.100.prop.men.40.50.F.40.50,
RMSE.error.infer.clust.cov.100.prop.women.25.40.M.40.50,
# RMSE.error.infer.clust.cov.100.prop.women.25.40.M.15.25,
RMSE.error.infer.clust.cov.100.prop.women.25.40.M.25.40,
# RMSE.error.infer.clust.cov.100.prop.men.25.40.F.40.50,
RMSE.error.infer.clust.cov.100.prop.men.25.40.F.15.25,
RMSE.error.infer.clust.cov.100.prop.men.25.40.F.25.40,
RMSE.error.infer.clust.cov.100.prop.women.15.25.M.40.50,
RMSE.error.infer.clust.cov.100.prop.women.15.25.M.25.40,
RMSE.error.infer.clust.cov.100.prop.women.15.25.M.15.25,
# RMSE.error.infer.clust.cov.100.prop.men.15.25.F.40.50,
# RMSE.error.infer.clust.cov.100.prop.men.15.25.F.25.40,
RMSE.error.infer.clust.cov.100.prop.men.15.25.F.15.25
)
d <- df_gps
newdata <- d[order(d$param),]
newdata$f_m <- c(rep("Females_Males", nrow(newdata)/2), rep("Males_Females", nrow(newdata)/2))
newdata$age_groups <- c(rep("15_24 & 15_24", 13), rep("15_24 & 25_39", 13), rep("15_24 & 40_49", 13), rep("25_39 & 25_39", 13), rep("25_39 & 40_49", 13),
rep("15_24 & 15_24", 13), rep("15_24 & 25_39", 13), rep("25_39 & 25_39", 13), rep("15_24 & 40_49", 13), rep("25_39 & 40_49", 13))
colnames(newdata) <- c("cov", "val", "param", "f_m", "age_groups")
saveRDS(newdata, file = "/home/david/age_mixing_patterns_phylogenetic/results/MAR_a/MAR_a_10_Error_for_Proportions_of_Pairings.RDS")
plot.prop_pairings_seq_cov_errors_100 <- ggplot(newdata, aes(x=cov, y=val, colour= age_groups, group = age_groups)) +
geom_line(size=1) +
geom_point() +
facet_grid(. ~ f_m) +
# theme(legend.position="top")+
xlab("Sampling Coverage (%)") + ylab("Error value for proportion of pairings")
print(plot.prop_pairings_seq_cov_errors_100)
ggsave(filename = "Plot_a_10_Error_for_Proportions_of_Pairings.pdf",
plot = plot.prop_pairings_seq_cov_errors_100,
path = "/home/david/age_mixing_patterns_phylogenetic/results/MAR_a",
width = 26, height = 15, units = "cm")
pdf("/home/david/age_mixing_patterns_phylogenetic/results/MAR_a/Plot_a_9_10_proportion_pairings_and_error_at_35_95_Coverage.pdf",
width=15, height=15)
gridExtra::grid.arrange(plot.prop_pairings_seq_cov_target_v, plot.prop_pairings_seq_cov_errors_100)
dev.off()## png
## 25 Age difference in pairings from transmission clusters
From pairings, knowing the age of each individual, we can be able to compute the age difference between man and woman within same pair. This means we consider the age difference for each man/woman in a certain age group with same pair with a woman/man.
5.1 True age difference at 100% sampling (sequence) coverage
Within 35 - 40 simulation, hen we consider 100% sampling (sequence) coverage, the average of age difference between pairs are given in the following table:
AD.true.cov.100 <- dr.cov.100 %>%
select(contains(".AD."))
## Vector
# Mean
vector.mean.AD.num.women.true.cov.100.15.25 <- AD.true.cov.100[,1] # AD.true.cov.100[,1]
vector.mean.AD.num.men.true.cov.100.15.25 <- AD.true.cov.100[,2] # AD.true.cov.100[,2]
vector.mean.AD.num.women.true.cov.100.25.40 <- AD.true.cov.100[,3] # AD.true.cov.100[,3]
vector.mean.AD.num.men.true.cov.100.25.40 <- AD.true.cov.100[,4] # AD.true.cov.100[,4]
vector.mean.AD.num.women.true.cov.100.40.50 <- AD.true.cov.100[,5] # AD.true.cov.100[,5]
vector.mean.AD.num.men.true.cov.100.40.50 <- AD.true.cov.100[,6] # AD.true.cov.100[,6]
# Median
vector.med.AD.num.women.true.cov.100.15.25 <- AD.true.cov.100[,7] # AD.true.cov.100[,7]
vector.med.AD.num.men.true.cov.100.15.25 <- AD.true.cov.100[,8] # AD.true.cov.100[,8]
vector.med.AD.num.women.true.cov.100.25.40 <- AD.true.cov.100[,9] # AD.true.cov.100[,9]
vector.med.AD.num.men.true.cov.100.25.40 <- AD.true.cov.100[,10] # AD.true.cov.100[,10]
vector.med.AD.num.women.true.cov.100.40.50 <- AD.true.cov.100[,11] # AD.true.cov.100[,11]
vector.med.AD.num.men.true.cov.100.40.50 <- AD.true.cov.100[,12] # AD.true.cov.100[,12]
# Standard deviation
vector.sd.AD.num.women.true.cov.100.15.25 <- AD.true.cov.100[,13] # AD.true.cov.100[,13]
vector.sd.AD.num.men.true.cov.100.15.25 <- AD.true.cov.100[,14] # AD.true.cov.100[,14]
vector.sd.AD.num.women.true.cov.100.25.40 <- AD.true.cov.100[,15] # AD.true.cov.100[,15]
vector.sd.AD.num.men.true.cov.100.25.40 <- AD.true.cov.100[,16] # AD.true.cov.100[,16]
vector.sd.AD.num.women.true.cov.100.40.50 <- AD.true.cov.100[,17] # AD.true.cov.100[,17]
vector.sd.AD.num.men.true.cov.100.40.50 <- AD.true.cov.100[,18] # AD.true.cov.100[,18]
# Summarised
# Mean
mean.AD.num.women.true.cov.100.15.25 <- quant.med(AD.true.cov.100[,1])
mean.AD.num.men.true.cov.100.15.25 <- quant.med(AD.true.cov.100[,2])
mean.AD.num.women.true.cov.100.25.40 <- quant.med(AD.true.cov.100[,3])
mean.AD.num.men.true.cov.100.25.40 <- quant.med(AD.true.cov.100[,4])
mean.AD.num.women.true.cov.100.40.50 <- quant.med(AD.true.cov.100[,5])
mean.AD.num.men.true.cov.100.40.50 <- quant.med(AD.true.cov.100[,6])
# Median
med.AD.num.women.true.cov.100.15.25 <- quant.med(AD.true.cov.100[,7])
med.AD.num.men.true.cov.100.15.25 <- quant.med(AD.true.cov.100[,8])
med.AD.num.women.true.cov.100.25.40 <- quant.med(AD.true.cov.100[,9])
med.AD.num.men.true.cov.100.25.40 <- quant.med(AD.true.cov.100[,10])
med.AD.num.women.true.cov.100.40.50 <- quant.med(AD.true.cov.100[,11])
med.AD.num.men.true.cov.100.40.50 <- quant.med(AD.true.cov.100[,12])
# Standard deviation
sd.AD.num.women.true.cov.100.15.25 <- quant.med(AD.true.cov.100[,13])
sd.AD.num.men.true.cov.100.15.25 <- quant.med(AD.true.cov.100[,14])
sd.AD.num.women.true.cov.100.25.40 <- quant.med(AD.true.cov.100[,15])
sd.AD.num.men.true.cov.100.25.40 <- quant.med(AD.true.cov.100[,16])
sd.AD.num.women.true.cov.100.40.50 <- quant.med(AD.true.cov.100[,17])
sd.AD.num.men.true.cov.100.40.50 <- quant.med(AD.true.cov.100[,18])
# Table of true AD statistics ta 100% coverage --------
AD.100.val.F <- c(mean.AD.num.women.true.cov.100.15.25[2], mean.AD.num.men.true.cov.100.15.25[2],
mean.AD.num.women.true.cov.100.25.40[2], mean.AD.num.men.true.cov.100.25.40[2],
mean.AD.num.women.true.cov.100.40.50[2], mean.AD.num.men.true.cov.100.40.50[2],
med.AD.num.women.true.cov.100.15.25[2], med.AD.num.men.true.cov.100.15.25[2],
med.AD.num.women.true.cov.100.25.40[2], med.AD.num.men.true.cov.100.25.40[2],
med.AD.num.women.true.cov.100.40.50[2], med.AD.num.men.true.cov.100.40.50[2],
sd.AD.num.women.true.cov.100.15.25[2], sd.AD.num.men.true.cov.100.15.25[2],
sd.AD.num.women.true.cov.100.25.40[2], sd.AD.num.men.true.cov.100.25.40[2],
sd.AD.num.women.true.cov.100.40.50[2], sd.AD.num.men.true.cov.100.40.50[2])
AD.100.val.U <- c(mean.AD.num.women.true.cov.100.15.25[3], mean.AD.num.men.true.cov.100.15.25[3],
mean.AD.num.women.true.cov.100.25.40[3], mean.AD.num.men.true.cov.100.25.40[3],
mean.AD.num.women.true.cov.100.40.50[3], mean.AD.num.men.true.cov.100.40.50[3],
med.AD.num.women.true.cov.100.15.25[3], med.AD.num.men.true.cov.100.15.25[3],
med.AD.num.women.true.cov.100.25.40[3], med.AD.num.men.true.cov.100.25.40[3],
med.AD.num.women.true.cov.100.40.50[3], med.AD.num.men.true.cov.100.40.50[3],
sd.AD.num.women.true.cov.100.15.25[3], sd.AD.num.men.true.cov.100.15.25[3],
sd.AD.num.women.true.cov.100.25.40[3], sd.AD.num.men.true.cov.100.25.40[3],
sd.AD.num.women.true.cov.100.40.50[3], sd.AD.num.men.true.cov.100.40.50[3])
AD.100.val.L <- c(mean.AD.num.women.true.cov.100.15.25[1], mean.AD.num.men.true.cov.100.15.25[1],
mean.AD.num.women.true.cov.100.25.40[1], mean.AD.num.men.true.cov.100.25.40[1],
mean.AD.num.women.true.cov.100.40.50[1], mean.AD.num.men.true.cov.100.40.50[1],
med.AD.num.women.true.cov.100.15.25[1], med.AD.num.men.true.cov.100.15.25[1],
med.AD.num.women.true.cov.100.25.40[1], med.AD.num.men.true.cov.100.25.40[1],
med.AD.num.women.true.cov.100.40.50[1], med.AD.num.men.true.cov.100.40.50[1],
sd.AD.num.women.true.cov.100.15.25[1], sd.AD.num.men.true.cov.100.15.25[1],
sd.AD.num.women.true.cov.100.25.40[1], sd.AD.num.men.true.cov.100.25.40[1],
sd.AD.num.women.true.cov.100.40.50[1], sd.AD.num.men.true.cov.100.40.50[1])
names.AD <- c("mean.AD.women.cl.15.25", "mean.AD.men.cl.15.25",
"mean.AD.women.cl.25.40", "mean.AD.men.cl.25.40",
"mean.AD.women.cl.40.50", "mean.AD.men.cl.40.50",
"med.AD.women.cl.15.25", "med.AD.men.cl.15.25",
"med.AD.women.cl.25.40", "med.AD.men.cl.25.40",
"med.AD.women.cl.40.50", "med.AD.men.cl.40.50",
"sd.AD.women.cl.15.25", "sd.AD.men.cl.15.25",
"sd.AD.women.cl.25.40", "sd.AD.men.cl.25.40",
"sd.AD.women.cl.40.50", "sd.AD.men.cl.40.50")
AD_100 <- data.frame(names.AD, AD.100.val.L, AD.100.val.F, AD.100.val.U)
colnames(AD_100) <- c("name", "lower.Q1", "med", "upper.Q3")
AD_100 %>%
kable() %>%
kable_styling("striped") | name | lower.Q1 | med | upper.Q3 |
|---|---|---|---|
| mean.AD.women.cl.15.25 | 11.407641 | 13.211441 | 15.024150 |
| mean.AD.men.cl.15.25 | 2.311600 | 2.910712 | 3.602536 |
| mean.AD.women.cl.25.40 | 11.842918 | 13.697393 | 15.582854 |
| mean.AD.men.cl.25.40 | 10.410999 | 11.458548 | 12.440997 |
| mean.AD.women.cl.40.50 | 3.427958 | 4.654275 | 7.064057 |
| mean.AD.men.cl.40.50 | 19.171094 | 20.350407 | 21.330128 |
| med.AD.women.cl.15.25 | 10.624465 | 13.064810 | 15.699235 |
| med.AD.men.cl.15.25 | 1.912691 | 2.717614 | 3.524021 |
| med.AD.women.cl.25.40 | 12.159128 | 14.566359 | 16.146174 |
| med.AD.men.cl.25.40 | 10.275718 | 11.439360 | 12.647079 |
| med.AD.women.cl.40.50 | 2.749416 | 4.346216 | 7.064057 |
| med.AD.men.cl.40.50 | 19.137103 | 20.490878 | 21.654009 |
| sd.AD.women.cl.15.25 | 6.245969 | 6.924548 | 7.641426 |
| sd.AD.men.cl.15.25 | 1.439109 | 1.876773 | 2.245871 |
| sd.AD.women.cl.25.40 | 3.498206 | 5.032506 | 6.243293 |
| sd.AD.men.cl.25.40 | 3.724295 | 4.183783 | 4.629266 |
| sd.AD.women.cl.40.50 | 1.978635 | 2.534065 | 3.847012 |
| sd.AD.men.cl.40.50 | 3.199840 | 3.763976 | 4.440838 |
write.csv(AD_100, file = "/home/david/age_mixing_patterns_phylogenetic/results/MAR_a/Table_a_15_True_Age_Difference_100_Coverage.csv")5.2 Age difference in different sequence coverage scenarios within pairings inferred from phylogenetic tree
AD.MAR.cov.35 <- d.MAR.cov.35 %>%
select(contains(".AD."))
AD.MAR.cov.40 <- d.MAR.cov.40 %>%
select(contains(".AD."))
AD.MAR.cov.45 <- d.MAR.cov.45 %>%
select(contains(".AD."))
AD.MAR.cov.50 <- d.MAR.cov.50 %>%
select(contains(".AD."))
AD.MAR.cov.55 <- d.MAR.cov.55 %>%
select(contains(".AD."))
AD.MAR.cov.60 <- d.MAR.cov.60 %>%
select(contains(".AD."))
AD.MAR.cov.65 <- d.MAR.cov.65 %>%
select(contains(".AD."))
AD.MAR.cov.70 <- d.MAR.cov.70 %>%
select(contains(".AD."))
AD.MAR.cov.75 <- d.MAR.cov.75 %>%
select(contains(".AD."))
AD.MAR.cov.80 <- d.MAR.cov.80 %>%
select(contains(".AD."))
AD.MAR.cov.85 <- d.MAR.cov.85 %>%
select(contains(".AD."))
AD.MAR.cov.90 <- d.MAR.cov.90 %>%
select(contains(".AD."))
AD.MAR.cov.95 <- d.MAR.cov.95 %>%
select(contains(".AD."))
# Statistics of age difference of individuals's true pairings at 100% coverage
AD.true.cov.100 <- dr.cov.100 %>%
select(contains(".AD."))
## Vector
# Mean
vector.mean.AD.num.women.true.cov.100.15.25 <- AD.true.cov.100[,1] # AD.true.cov.100[,1]
vector.mean.AD.num.men.true.cov.100.15.25 <- AD.true.cov.100[,2] # AD.true.cov.100[,2]
vector.mean.AD.num.women.true.cov.100.25.40 <- AD.true.cov.100[,3] # AD.true.cov.100[,3]
vector.mean.AD.num.men.true.cov.100.25.40 <- AD.true.cov.100[,4] # AD.true.cov.100[,4]
vector.mean.AD.num.women.true.cov.100.40.50 <- AD.true.cov.100[,5] # AD.true.cov.100[,5]
vector.mean.AD.num.men.true.cov.100.40.50 <- AD.true.cov.100[,6] # AD.true.cov.100[,6]
# Median
vector.med.AD.num.women.true.cov.100.15.25 <- AD.true.cov.100[,7] # AD.true.cov.100[,7]
vector.med.AD.num.men.true.cov.100.15.25 <- AD.true.cov.100[,8] # AD.true.cov.100[,8]
vector.med.AD.num.women.true.cov.100.25.40 <- AD.true.cov.100[,9] # AD.true.cov.100[,9]
vector.med.AD.num.men.true.cov.100.25.40 <- AD.true.cov.100[,10] # AD.true.cov.100[,10]
vector.med.AD.num.women.true.cov.100.40.50 <- AD.true.cov.100[,11] # AD.true.cov.100[,11]
vector.med.AD.num.men.true.cov.100.40.50 <- AD.true.cov.100[,12] # AD.true.cov.100[,12]
# Standard deviation
vector.sd.AD.num.women.true.cov.100.15.25 <- AD.true.cov.100[,13] # AD.true.cov.100[,13]
vector.sd.AD.num.men.true.cov.100.15.25 <- AD.true.cov.100[,14] # AD.true.cov.100[,14]
vector.sd.AD.num.women.true.cov.100.25.40 <- AD.true.cov.100[,15] # AD.true.cov.100[,15]
vector.sd.AD.num.men.true.cov.100.25.40 <- AD.true.cov.100[,16] # AD.true.cov.100[,16]
vector.sd.AD.num.women.true.cov.100.40.50 <- AD.true.cov.100[,17] # AD.true.cov.100[,17]
vector.sd.AD.num.men.true.cov.100.40.50 <- AD.true.cov.100[,18] # AD.true.cov.100[,18]
# Summarised
# Mean
mean.AD.num.women.true.cov.100.15.25 <- quant.med(AD.true.cov.100[,1])
mean.AD.num.men.true.cov.100.15.25 <- quant.med(AD.true.cov.100[,2])
mean.AD.num.women.true.cov.100.25.40 <- quant.med(AD.true.cov.100[,3])
mean.AD.num.men.true.cov.100.25.40 <- quant.med(AD.true.cov.100[,4])
mean.AD.num.women.true.cov.100.40.50 <- quant.med(AD.true.cov.100[,5])
mean.AD.num.men.true.cov.100.40.50 <- quant.med(AD.true.cov.100[,6])
# Median
med.AD.num.women.true.cov.100.15.25 <- quant.med(AD.true.cov.100[,7])
med.AD.num.men.true.cov.100.15.25 <- quant.med(AD.true.cov.100[,8])
med.AD.num.women.true.cov.100.25.40 <- quant.med(AD.true.cov.100[,9])
med.AD.num.men.true.cov.100.25.40 <- quant.med(AD.true.cov.100[,10])
med.AD.num.women.true.cov.100.40.50 <- quant.med(AD.true.cov.100[,11])
med.AD.num.men.true.cov.100.40.50 <- quant.med(AD.true.cov.100[,12])
# Standard deviation
sd.AD.num.women.true.cov.100.15.25 <- quant.med(AD.true.cov.100[,13])
sd.AD.num.men.true.cov.100.15.25 <- quant.med(AD.true.cov.100[,14])
sd.AD.num.women.true.cov.100.25.40 <- quant.med(AD.true.cov.100[,15])
sd.AD.num.men.true.cov.100.25.40 <- quant.med(AD.true.cov.100[,16])
sd.AD.num.women.true.cov.100.40.50 <- quant.med(AD.true.cov.100[,17])
sd.AD.num.men.true.cov.100.40.50 <- quant.med(AD.true.cov.100[,18])
# Statistics of age difference for individuals' in pairings from transmission clusters
# Cov 35
## Vector
# Mean
vector.mean.MAR.cov.35.AD.women.cl.15.25 <- AD.MAR.cov.35[,1]
vector.mean.MAR.cov.35.AD.men.cl.15.25 <- AD.MAR.cov.35[,2]
vector.mean.MAR.cov.35.AD.women.cl.25.40 <- AD.MAR.cov.35[,3]
vector.mean.MAR.cov.35.AD.men.cl.25.40 <- AD.MAR.cov.35[,4]
vector.mean.MAR.cov.35.AD.women.cl.40.50 <- AD.MAR.cov.35[,5]
vector.mean.MAR.cov.35.AD.men.cl.40.50 <- AD.MAR.cov.35[,6]
# Median
vector.med.MAR.cov.35.AD.women.cl.15.25 <- AD.MAR.cov.35[,7]
vector.med.MAR.cov.35.AD.men.cl.15.25 <- AD.MAR.cov.35[,8]
vector.med.MAR.cov.35.AD.women.cl.25.40 <- AD.MAR.cov.35[,9]
vector.med.MAR.cov.35.AD.men.cl.25.40 <- AD.MAR.cov.35[,10]
vector.med.MAR.cov.35.AD.women.cl.40.50 <- AD.MAR.cov.35[,11]
vector.med.MAR.cov.35.AD.men.cl.40.50 <- AD.MAR.cov.35[,12]
# Standard deviation
vector.sd.MAR.cov.35.AD.women.cl.15.25 <- AD.MAR.cov.35[,13]
vector.sd.MAR.cov.35.AD.men.cl.15.25 <- AD.MAR.cov.35[,14]
vector.sd.MAR.cov.35.AD.women.cl.25.40 <- AD.MAR.cov.35[,15]
vector.sd.MAR.cov.35.AD.men.cl.25.40 <- AD.MAR.cov.35[,16]
vector.sd.MAR.cov.35.AD.women.cl.40.50 <- AD.MAR.cov.35[,17]
vector.sd.MAR.cov.35.AD.men.cl.40.50 <- AD.MAR.cov.35[,18]
## Summarised
# Mean
mean.MAR.cov.35.AD.women.cl.15.25 <- quant.med(AD.MAR.cov.35[,1])
mean.MAR.cov.35.AD.men.cl.15.25 <- quant.med(AD.MAR.cov.35[,2])
mean.MAR.cov.35.AD.women.cl.25.40 <- quant.med(AD.MAR.cov.35[,3])
mean.MAR.cov.35.AD.men.cl.25.40 <- quant.med(AD.MAR.cov.35[,4])
mean.MAR.cov.35.AD.women.cl.40.50 <- quant.med(AD.MAR.cov.35[,5])
mean.MAR.cov.35.AD.men.cl.40.50 <- quant.med(AD.MAR.cov.35[,6])
# Median
med.MAR.cov.35.AD.women.cl.15.25 <- quant.med(AD.MAR.cov.35[,7])
med.MAR.cov.35.AD.men.cl.15.25 <- quant.med(AD.MAR.cov.35[,8])
med.MAR.cov.35.AD.women.cl.25.40 <- quant.med(AD.MAR.cov.35[,9])
med.MAR.cov.35.AD.men.cl.25.40 <- quant.med(AD.MAR.cov.35[,10])
med.MAR.cov.35.AD.women.cl.40.50 <- quant.med(AD.MAR.cov.35[,11])
med.MAR.cov.35.AD.men.cl.40.50 <- quant.med(AD.MAR.cov.35[,12])
# Standard deviation
sd.MAR.cov.35.AD.women.cl.15.25 <- quant.med(AD.MAR.cov.35[,13])
sd.MAR.cov.35.AD.men.cl.15.25 <- quant.med(AD.MAR.cov.35[,14])
sd.MAR.cov.35.AD.women.cl.25.40 <- quant.med(AD.MAR.cov.35[,15])
sd.MAR.cov.35.AD.men.cl.25.40 <- quant.med(AD.MAR.cov.35[,16])
sd.MAR.cov.35.AD.women.cl.40.50 <- quant.med(AD.MAR.cov.35[,17])
sd.MAR.cov.35.AD.men.cl.40.50 <- quant.med(AD.MAR.cov.35[,18])
# Cov 40
## Vector
# Mean
vector.mean.MAR.cov.40.AD.women.cl.15.25 <- AD.MAR.cov.40[,1]
vector.mean.MAR.cov.40.AD.men.cl.15.25 <- AD.MAR.cov.40[,2]
vector.mean.MAR.cov.40.AD.women.cl.25.40 <- AD.MAR.cov.40[,3]
vector.mean.MAR.cov.40.AD.men.cl.25.40 <- AD.MAR.cov.40[,4]
vector.mean.MAR.cov.40.AD.women.cl.40.50 <- AD.MAR.cov.40[,5]
vector.mean.MAR.cov.40.AD.men.cl.40.50 <- AD.MAR.cov.40[,6]
# Median
vector.med.MAR.cov.40.AD.women.cl.15.25 <- AD.MAR.cov.40[,7]
vector.med.MAR.cov.40.AD.men.cl.15.25 <- AD.MAR.cov.40[,8]
vector.med.MAR.cov.40.AD.women.cl.25.40 <- AD.MAR.cov.40[,9]
vector.med.MAR.cov.40.AD.men.cl.25.40 <- AD.MAR.cov.40[,10]
vector.med.MAR.cov.40.AD.women.cl.40.50 <- AD.MAR.cov.40[,11]
vector.med.MAR.cov.40.AD.men.cl.40.50 <- AD.MAR.cov.40[,12]
# Standard deviation
vector.sd.MAR.cov.40.AD.women.cl.15.25 <- AD.MAR.cov.40[,13]
vector.sd.MAR.cov.40.AD.men.cl.15.25 <- AD.MAR.cov.40[,14]
vector.sd.MAR.cov.40.AD.women.cl.25.40 <- AD.MAR.cov.40[,15]
vector.sd.MAR.cov.40.AD.men.cl.25.40 <- AD.MAR.cov.40[,16]
vector.sd.MAR.cov.40.AD.women.cl.40.50 <- AD.MAR.cov.40[,17]
vector.sd.MAR.cov.40.AD.men.cl.40.50 <- AD.MAR.cov.40[,18]
## Summarised
# Mean
mean.MAR.cov.40.AD.women.cl.15.25 <- quant.med(AD.MAR.cov.40[,1])
mean.MAR.cov.40.AD.men.cl.15.25 <- quant.med(AD.MAR.cov.40[,2])
mean.MAR.cov.40.AD.women.cl.25.40 <- quant.med(AD.MAR.cov.40[,3])
mean.MAR.cov.40.AD.men.cl.25.40 <- quant.med(AD.MAR.cov.40[,4])
mean.MAR.cov.40.AD.women.cl.40.50 <- quant.med(AD.MAR.cov.40[,5])
mean.MAR.cov.40.AD.men.cl.40.50 <- quant.med(AD.MAR.cov.40[,6])
# Median
med.MAR.cov.40.AD.women.cl.15.25 <- quant.med(AD.MAR.cov.40[,7])
med.MAR.cov.40.AD.men.cl.15.25 <- quant.med(AD.MAR.cov.40[,8])
med.MAR.cov.40.AD.women.cl.25.40 <- quant.med(AD.MAR.cov.40[,9])
med.MAR.cov.40.AD.men.cl.25.40 <- quant.med(AD.MAR.cov.40[,10])
med.MAR.cov.40.AD.women.cl.40.50 <- quant.med(AD.MAR.cov.40[,11])
med.MAR.cov.40.AD.men.cl.40.50 <- quant.med(AD.MAR.cov.40[,12])
# Standard deviation
sd.MAR.cov.40.AD.women.cl.15.25 <- quant.med(AD.MAR.cov.40[,13])
sd.MAR.cov.40.AD.men.cl.15.25 <- quant.med(AD.MAR.cov.40[,14])
sd.MAR.cov.40.AD.women.cl.25.40 <- quant.med(AD.MAR.cov.40[,15])
sd.MAR.cov.40.AD.men.cl.25.40 <- quant.med(AD.MAR.cov.40[,16])
sd.MAR.cov.40.AD.women.cl.40.50 <- quant.med(AD.MAR.cov.40[,17])
sd.MAR.cov.40.AD.men.cl.40.50 <- quant.med(AD.MAR.cov.40[,18])
# Cov 45
# Vector
# Mean
vector.mean.MAR.cov.45.AD.women.cl.15.25 <- AD.MAR.cov.45[,1]
vector.mean.MAR.cov.45.AD.men.cl.15.25 <- AD.MAR.cov.45[,2]
vector.mean.MAR.cov.45.AD.women.cl.25.40 <- AD.MAR.cov.45[,3]
vector.mean.MAR.cov.45.AD.men.cl.25.40 <- AD.MAR.cov.45[,4]
vector.mean.MAR.cov.45.AD.women.cl.40.50 <- AD.MAR.cov.45[,5]
vector.mean.MAR.cov.45.AD.men.cl.40.50 <- AD.MAR.cov.45[,6]
# Median
vector.med.MAR.cov.45.AD.women.cl.15.25 <- AD.MAR.cov.45[,7]
vector.med.MAR.cov.45.AD.men.cl.15.25 <- AD.MAR.cov.45[,8]
vector.med.MAR.cov.45.AD.women.cl.25.40 <- AD.MAR.cov.45[,9]
vector.med.MAR.cov.45.AD.men.cl.25.40 <- AD.MAR.cov.45[,10]
vector.med.MAR.cov.45.AD.women.cl.40.50 <- AD.MAR.cov.45[,11]
vector.med.MAR.cov.45.AD.men.cl.40.50 <- AD.MAR.cov.45[,12]
# Standard deviation
vector.sd.MAR.cov.45.AD.women.cl.15.25 <- AD.MAR.cov.45[,13]
vector.sd.MAR.cov.45.AD.men.cl.15.25 <- AD.MAR.cov.45[,14]
vector.sd.MAR.cov.45.AD.women.cl.25.40 <- AD.MAR.cov.45[,15]
vector.sd.MAR.cov.45.AD.men.cl.25.40 <- AD.MAR.cov.45[,16]
vector.sd.MAR.cov.45.AD.women.cl.40.50 <- AD.MAR.cov.45[,17]
vector.sd.MAR.cov.45.AD.men.cl.40.50 <- AD.MAR.cov.45[,18]
## Summarised
# Mean
mean.MAR.cov.45.AD.women.cl.15.25 <- quant.med(AD.MAR.cov.45[,1])
mean.MAR.cov.45.AD.men.cl.15.25 <- quant.med(AD.MAR.cov.45[,2])
mean.MAR.cov.45.AD.women.cl.25.40 <- quant.med(AD.MAR.cov.45[,3])
mean.MAR.cov.45.AD.men.cl.25.40 <- quant.med(AD.MAR.cov.45[,4])
mean.MAR.cov.45.AD.women.cl.40.50 <- quant.med(AD.MAR.cov.45[,5])
mean.MAR.cov.45.AD.men.cl.40.50 <- quant.med(AD.MAR.cov.45[,6])
# Median
med.MAR.cov.45.AD.women.cl.15.25 <- quant.med(AD.MAR.cov.45[,7])
med.MAR.cov.45.AD.men.cl.15.25 <- quant.med(AD.MAR.cov.45[,8])
med.MAR.cov.45.AD.women.cl.25.40 <- quant.med(AD.MAR.cov.45[,9])
med.MAR.cov.45.AD.men.cl.25.40 <- quant.med(AD.MAR.cov.45[,10])
med.MAR.cov.45.AD.women.cl.40.50 <- quant.med(AD.MAR.cov.45[,11])
med.MAR.cov.45.AD.men.cl.40.50 <- quant.med(AD.MAR.cov.45[,12])
# Standard deviation
sd.MAR.cov.45.AD.women.cl.15.25 <- quant.med(AD.MAR.cov.45[,13])
sd.MAR.cov.45.AD.men.cl.15.25 <- quant.med(AD.MAR.cov.45[,14])
sd.MAR.cov.45.AD.women.cl.25.40 <- quant.med(AD.MAR.cov.45[,15])
sd.MAR.cov.45.AD.men.cl.25.40 <- quant.med(AD.MAR.cov.45[,16])
sd.MAR.cov.45.AD.women.cl.40.50 <- quant.med(AD.MAR.cov.45[,17])
sd.MAR.cov.45.AD.men.cl.40.50 <- quant.med(AD.MAR.cov.45[,18])
# Cov 50
## Vector
# Mean
vector.mean.MAR.cov.50.AD.women.cl.15.25 <- AD.MAR.cov.50[,1]
vector.mean.MAR.cov.50.AD.men.cl.15.25 <- AD.MAR.cov.50[,2]
vector.mean.MAR.cov.50.AD.women.cl.25.40 <- AD.MAR.cov.50[,3]
vector.mean.MAR.cov.50.AD.men.cl.25.40 <- AD.MAR.cov.50[,4]
vector.mean.MAR.cov.50.AD.women.cl.40.50 <- AD.MAR.cov.50[,5]
vector.mean.MAR.cov.50.AD.men.cl.40.50 <- AD.MAR.cov.50[,6]
# Median
vector.med.MAR.cov.50.AD.women.cl.15.25 <- AD.MAR.cov.50[,7]
vector.med.MAR.cov.50.AD.men.cl.15.25 <- AD.MAR.cov.50[,8]
vector.med.MAR.cov.50.AD.women.cl.25.40 <- AD.MAR.cov.50[,9]
vector.med.MAR.cov.50.AD.men.cl.25.40 <- AD.MAR.cov.50[,10]
vector.med.MAR.cov.50.AD.women.cl.40.50 <- AD.MAR.cov.50[,11]
vector.med.MAR.cov.50.AD.men.cl.40.50 <- AD.MAR.cov.50[,12]
# Standard deviation
vector.sd.MAR.cov.50.AD.women.cl.15.25 <- AD.MAR.cov.50[,13]
vector.sd.MAR.cov.50.AD.men.cl.15.25 <- AD.MAR.cov.50[,14]
vector.sd.MAR.cov.50.AD.women.cl.25.40 <- AD.MAR.cov.50[,15]
vector.sd.MAR.cov.50.AD.men.cl.25.40 <- AD.MAR.cov.50[,16]
vector.sd.MAR.cov.50.AD.women.cl.40.50 <- AD.MAR.cov.50[,17]
vector.sd.MAR.cov.50.AD.men.cl.40.50 <- AD.MAR.cov.50[,18]
## Summarised
# Mean
mean.MAR.cov.50.AD.women.cl.15.25 <- quant.med(AD.MAR.cov.50[,1])
mean.MAR.cov.50.AD.men.cl.15.25 <- quant.med(AD.MAR.cov.50[,2])
mean.MAR.cov.50.AD.women.cl.25.40 <- quant.med(AD.MAR.cov.50[,3])
mean.MAR.cov.50.AD.men.cl.25.40 <- quant.med(AD.MAR.cov.50[,4])
mean.MAR.cov.50.AD.women.cl.40.50 <- quant.med(AD.MAR.cov.50[,5])
mean.MAR.cov.50.AD.men.cl.40.50 <- quant.med(AD.MAR.cov.50[,6])
# Median
med.MAR.cov.50.AD.women.cl.15.25 <- quant.med(AD.MAR.cov.50[,7])
med.MAR.cov.50.AD.men.cl.15.25 <- quant.med(AD.MAR.cov.50[,8])
med.MAR.cov.50.AD.women.cl.25.40 <- quant.med(AD.MAR.cov.50[,9])
med.MAR.cov.50.AD.men.cl.25.40 <- quant.med(AD.MAR.cov.50[,10])
med.MAR.cov.50.AD.women.cl.40.50 <- quant.med(AD.MAR.cov.50[,11])
med.MAR.cov.50.AD.men.cl.40.50 <- quant.med(AD.MAR.cov.50[,12])
# Standard deviation
sd.MAR.cov.50.AD.women.cl.15.25 <- quant.med(AD.MAR.cov.50[,13])
sd.MAR.cov.50.AD.men.cl.15.25 <- quant.med(AD.MAR.cov.50[,14])
sd.MAR.cov.50.AD.women.cl.25.40 <- quant.med(AD.MAR.cov.50[,15])
sd.MAR.cov.50.AD.men.cl.25.40 <- quant.med(AD.MAR.cov.50[,16])
sd.MAR.cov.50.AD.women.cl.40.50 <- quant.med(AD.MAR.cov.50[,17])
sd.MAR.cov.50.AD.men.cl.40.50 <- quant.med(AD.MAR.cov.50[,18])
# Cov 55
## Vector
# Mean
vector.mean.MAR.cov.55.AD.women.cl.15.25 <- AD.MAR.cov.55[,1]
vector.mean.MAR.cov.55.AD.men.cl.15.25 <- AD.MAR.cov.55[,2]
vector.mean.MAR.cov.55.AD.women.cl.25.40 <- AD.MAR.cov.55[,3]
vector.mean.MAR.cov.55.AD.men.cl.25.40 <- AD.MAR.cov.55[,4]
vector.mean.MAR.cov.55.AD.women.cl.40.50 <- AD.MAR.cov.55[,5]
vector.mean.MAR.cov.55.AD.men.cl.40.50 <- AD.MAR.cov.55[,6]
# Median
vector.med.MAR.cov.55.AD.women.cl.15.25 <- AD.MAR.cov.55[,7]
vector.med.MAR.cov.55.AD.men.cl.15.25 <- AD.MAR.cov.55[,8]
vector.med.MAR.cov.55.AD.women.cl.25.40 <- AD.MAR.cov.55[,9]
vector.med.MAR.cov.55.AD.men.cl.25.40 <- AD.MAR.cov.55[,10]
vector.med.MAR.cov.55.AD.women.cl.40.50 <- AD.MAR.cov.55[,11]
vector.med.MAR.cov.55.AD.men.cl.40.50 <- AD.MAR.cov.55[,12]
# Standard deviation
vector.sd.MAR.cov.55.AD.women.cl.15.25 <- AD.MAR.cov.55[,13]
vector.sd.MAR.cov.55.AD.men.cl.15.25 <- AD.MAR.cov.55[,14]
vector.sd.MAR.cov.55.AD.women.cl.25.40 <- AD.MAR.cov.55[,15]
vector.sd.MAR.cov.55.AD.men.cl.25.40 <- AD.MAR.cov.55[,16]
vector.sd.MAR.cov.55.AD.women.cl.40.50 <- AD.MAR.cov.55[,17]
vector.sd.MAR.cov.55.AD.men.cl.40.50 <- AD.MAR.cov.55[,18]
## Summarised
# Mean
mean.MAR.cov.55.AD.women.cl.15.25 <- quant.med(AD.MAR.cov.55[,1])
mean.MAR.cov.55.AD.men.cl.15.25 <- quant.med(AD.MAR.cov.55[,2])
mean.MAR.cov.55.AD.women.cl.25.40 <- quant.med(AD.MAR.cov.55[,3])
mean.MAR.cov.55.AD.men.cl.25.40 <- quant.med(AD.MAR.cov.55[,4])
mean.MAR.cov.55.AD.women.cl.40.50 <- quant.med(AD.MAR.cov.55[,5])
mean.MAR.cov.55.AD.men.cl.40.50 <- quant.med(AD.MAR.cov.55[,6])
# Median
med.MAR.cov.55.AD.women.cl.15.25 <- quant.med(AD.MAR.cov.55[,7])
med.MAR.cov.55.AD.men.cl.15.25 <- quant.med(AD.MAR.cov.55[,8])
med.MAR.cov.55.AD.women.cl.25.40 <- quant.med(AD.MAR.cov.55[,9])
med.MAR.cov.55.AD.men.cl.25.40 <- quant.med(AD.MAR.cov.55[,10])
med.MAR.cov.55.AD.women.cl.40.50 <- quant.med(AD.MAR.cov.55[,11])
med.MAR.cov.55.AD.men.cl.40.50 <- quant.med(AD.MAR.cov.55[,12])
# Standard deviation
sd.MAR.cov.55.AD.women.cl.15.25 <- quant.med(AD.MAR.cov.55[,13])
sd.MAR.cov.55.AD.men.cl.15.25 <- quant.med(AD.MAR.cov.55[,14])
sd.MAR.cov.55.AD.women.cl.25.40 <- quant.med(AD.MAR.cov.55[,15])
sd.MAR.cov.55.AD.men.cl.25.40 <- quant.med(AD.MAR.cov.55[,16])
sd.MAR.cov.55.AD.women.cl.40.50 <- quant.med(AD.MAR.cov.55[,17])
sd.MAR.cov.55.AD.men.cl.40.50 <- quant.med(AD.MAR.cov.55[,18])
# Cov 60
## Vector
# Mean
vector.mean.MAR.cov.60.AD.women.cl.15.25 <- AD.MAR.cov.60[,1]
vector.mean.MAR.cov.60.AD.men.cl.15.25 <- AD.MAR.cov.60[,2]
vector.mean.MAR.cov.60.AD.women.cl.25.40 <- AD.MAR.cov.60[,3]
vector.mean.MAR.cov.60.AD.men.cl.25.40 <- AD.MAR.cov.60[,4]
vector.mean.MAR.cov.60.AD.women.cl.40.50 <- AD.MAR.cov.60[,5]
vector.mean.MAR.cov.60.AD.men.cl.40.50 <- AD.MAR.cov.60[,6]
# Median
vector.med.MAR.cov.60.AD.women.cl.15.25 <- AD.MAR.cov.60[,7]
vector.med.MAR.cov.60.AD.men.cl.15.25 <- AD.MAR.cov.60[,8]
vector.med.MAR.cov.60.AD.women.cl.25.40 <- AD.MAR.cov.60[,9]
vector.med.MAR.cov.60.AD.men.cl.25.40 <- AD.MAR.cov.60[,10]
vector.med.MAR.cov.60.AD.women.cl.40.50 <- AD.MAR.cov.60[,11]
vector.med.MAR.cov.60.AD.men.cl.40.50 <- AD.MAR.cov.60[,12]
# Standard deviation
vector.sd.MAR.cov.60.AD.women.cl.15.25 <- AD.MAR.cov.60[,13]
vector.sd.MAR.cov.60.AD.men.cl.15.25 <- AD.MAR.cov.60[,14]
vector.sd.MAR.cov.60.AD.women.cl.25.40 <- AD.MAR.cov.60[,15]
vector.sd.MAR.cov.60.AD.men.cl.25.40 <- AD.MAR.cov.60[,16]
vector.sd.MAR.cov.60.AD.women.cl.40.50 <- AD.MAR.cov.60[,17]
vector.sd.MAR.cov.60.AD.men.cl.40.50 <- AD.MAR.cov.60[,18]
## Summarised
# Mean
mean.MAR.cov.60.AD.women.cl.15.25 <- quant.med(AD.MAR.cov.60[,1])
mean.MAR.cov.60.AD.men.cl.15.25 <- quant.med(AD.MAR.cov.60[,2])
mean.MAR.cov.60.AD.women.cl.25.40 <- quant.med(AD.MAR.cov.60[,3])
mean.MAR.cov.60.AD.men.cl.25.40 <- quant.med(AD.MAR.cov.60[,4])
mean.MAR.cov.60.AD.women.cl.40.50 <- quant.med(AD.MAR.cov.60[,5])
mean.MAR.cov.60.AD.men.cl.40.50 <- quant.med(AD.MAR.cov.60[,6])
# Median
med.MAR.cov.60.AD.women.cl.15.25 <- quant.med(AD.MAR.cov.60[,7])
med.MAR.cov.60.AD.men.cl.15.25 <- quant.med(AD.MAR.cov.60[,8])
med.MAR.cov.60.AD.women.cl.25.40 <- quant.med(AD.MAR.cov.60[,9])
med.MAR.cov.60.AD.men.cl.25.40 <- quant.med(AD.MAR.cov.60[,10])
med.MAR.cov.60.AD.women.cl.40.50 <- quant.med(AD.MAR.cov.60[,11])
med.MAR.cov.60.AD.men.cl.40.50 <- quant.med(AD.MAR.cov.60[,12])
# Standard deviation
sd.MAR.cov.60.AD.women.cl.15.25 <- quant.med(AD.MAR.cov.60[,13])
sd.MAR.cov.60.AD.men.cl.15.25 <- quant.med(AD.MAR.cov.60[,14])
sd.MAR.cov.60.AD.women.cl.25.40 <- quant.med(AD.MAR.cov.60[,15])
sd.MAR.cov.60.AD.men.cl.25.40 <- quant.med(AD.MAR.cov.60[,16])
sd.MAR.cov.60.AD.women.cl.40.50 <- quant.med(AD.MAR.cov.60[,17])
sd.MAR.cov.60.AD.men.cl.40.50 <- quant.med(AD.MAR.cov.60[,18])
# Cov 65
## Vector
# Mean
vector.mean.MAR.cov.65.AD.women.cl.15.25 <- AD.MAR.cov.65[,1]
vector.mean.MAR.cov.65.AD.men.cl.15.25 <- AD.MAR.cov.65[,2]
vector.mean.MAR.cov.65.AD.women.cl.25.40 <- AD.MAR.cov.65[,3]
vector.mean.MAR.cov.65.AD.men.cl.25.40 <- AD.MAR.cov.65[,4]
vector.mean.MAR.cov.65.AD.women.cl.40.50 <- AD.MAR.cov.65[,5]
vector.mean.MAR.cov.65.AD.men.cl.40.50 <- AD.MAR.cov.65[,6]
# Median
vector.med.MAR.cov.65.AD.women.cl.15.25 <- AD.MAR.cov.65[,7]
vector.med.MAR.cov.65.AD.men.cl.15.25 <- AD.MAR.cov.65[,8]
vector.med.MAR.cov.65.AD.women.cl.25.40 <- AD.MAR.cov.65[,9]
vector.med.MAR.cov.65.AD.men.cl.25.40 <- AD.MAR.cov.65[,10]
vector.med.MAR.cov.65.AD.women.cl.40.50 <- AD.MAR.cov.65[,11]
vector.med.MAR.cov.65.AD.men.cl.40.50 <- AD.MAR.cov.65[,12]
# Standard deviation
vector.sd.MAR.cov.65.AD.women.cl.15.25 <- AD.MAR.cov.65[,13]
vector.sd.MAR.cov.65.AD.men.cl.15.25 <- AD.MAR.cov.65[,14]
vector.sd.MAR.cov.65.AD.women.cl.25.40 <- AD.MAR.cov.65[,15]
vector.sd.MAR.cov.65.AD.men.cl.25.40 <- AD.MAR.cov.65[,16]
vector.sd.MAR.cov.65.AD.women.cl.40.50 <- AD.MAR.cov.65[,17]
vector.sd.MAR.cov.65.AD.men.cl.40.50 <- AD.MAR.cov.65[,18]
## Summarised
# Mean
mean.MAR.cov.65.AD.women.cl.15.25 <- quant.med(AD.MAR.cov.65[,1])
mean.MAR.cov.65.AD.men.cl.15.25 <- quant.med(AD.MAR.cov.65[,2])
mean.MAR.cov.65.AD.women.cl.25.40 <- quant.med(AD.MAR.cov.65[,3])
mean.MAR.cov.65.AD.men.cl.25.40 <- quant.med(AD.MAR.cov.65[,4])
mean.MAR.cov.65.AD.women.cl.40.50 <- quant.med(AD.MAR.cov.65[,5])
mean.MAR.cov.65.AD.men.cl.40.50 <- quant.med(AD.MAR.cov.65[,6])
# Median
med.MAR.cov.65.AD.women.cl.15.25 <- quant.med(AD.MAR.cov.65[,7])
med.MAR.cov.65.AD.men.cl.15.25 <- quant.med(AD.MAR.cov.65[,8])
med.MAR.cov.65.AD.women.cl.25.40 <- quant.med(AD.MAR.cov.65[,9])
med.MAR.cov.65.AD.men.cl.25.40 <- quant.med(AD.MAR.cov.65[,10])
med.MAR.cov.65.AD.women.cl.40.50 <- quant.med(AD.MAR.cov.65[,11])
med.MAR.cov.65.AD.men.cl.40.50 <- quant.med(AD.MAR.cov.65[,12])
# Standard deviation
sd.MAR.cov.65.AD.women.cl.15.25 <- quant.med(AD.MAR.cov.65[,13])
sd.MAR.cov.65.AD.men.cl.15.25 <- quant.med(AD.MAR.cov.65[,14])
sd.MAR.cov.65.AD.women.cl.25.40 <- quant.med(AD.MAR.cov.65[,15])
sd.MAR.cov.65.AD.men.cl.25.40 <- quant.med(AD.MAR.cov.65[,16])
sd.MAR.cov.65.AD.women.cl.40.50 <- quant.med(AD.MAR.cov.65[,17])
sd.MAR.cov.65.AD.men.cl.40.50 <- quant.med(AD.MAR.cov.65[,18])
# Cov 70
## Vector
# Mean
vector.mean.MAR.cov.70.AD.women.cl.15.25 <- AD.MAR.cov.70[,1]
vector.mean.MAR.cov.70.AD.men.cl.15.25 <- AD.MAR.cov.70[,2]
vector.mean.MAR.cov.70.AD.women.cl.25.40 <- AD.MAR.cov.70[,3]
vector.mean.MAR.cov.70.AD.men.cl.25.40 <- AD.MAR.cov.70[,4]
vector.mean.MAR.cov.70.AD.women.cl.40.50 <- AD.MAR.cov.70[,5]
vector.mean.MAR.cov.70.AD.men.cl.40.50 <- AD.MAR.cov.70[,6]
# Median
vector.med.MAR.cov.70.AD.women.cl.15.25 <- AD.MAR.cov.70[,7]
vector.med.MAR.cov.70.AD.men.cl.15.25 <- AD.MAR.cov.70[,8]
vector.med.MAR.cov.70.AD.women.cl.25.40 <- AD.MAR.cov.70[,9]
vector.med.MAR.cov.70.AD.men.cl.25.40 <- AD.MAR.cov.70[,10]
vector.med.MAR.cov.70.AD.women.cl.40.50 <- AD.MAR.cov.70[,11]
vector.med.MAR.cov.70.AD.men.cl.40.50 <- AD.MAR.cov.70[,12]
# Standard deviation
vector.sd.MAR.cov.70.AD.women.cl.15.25 <- AD.MAR.cov.70[,13]
vector.sd.MAR.cov.70.AD.men.cl.15.25 <- AD.MAR.cov.70[,14]
vector.sd.MAR.cov.70.AD.women.cl.25.40 <- AD.MAR.cov.70[,15]
vector.sd.MAR.cov.70.AD.men.cl.25.40 <- AD.MAR.cov.70[,16]
vector.sd.MAR.cov.70.AD.women.cl.40.50 <- AD.MAR.cov.70[,17]
vector.sd.MAR.cov.70.AD.men.cl.40.50 <- AD.MAR.cov.70[,18]
## Summarised
# Mean
mean.MAR.cov.70.AD.women.cl.15.25 <- quant.med(AD.MAR.cov.70[,1])
mean.MAR.cov.70.AD.men.cl.15.25 <- quant.med(AD.MAR.cov.70[,2])
mean.MAR.cov.70.AD.women.cl.25.40 <- quant.med(AD.MAR.cov.70[,3])
mean.MAR.cov.70.AD.men.cl.25.40 <- quant.med(AD.MAR.cov.70[,4])
mean.MAR.cov.70.AD.women.cl.40.50 <- quant.med(AD.MAR.cov.70[,5])
mean.MAR.cov.70.AD.men.cl.40.50 <- quant.med(AD.MAR.cov.70[,6])
# Median
med.MAR.cov.70.AD.women.cl.15.25 <- quant.med(AD.MAR.cov.70[,7])
med.MAR.cov.70.AD.men.cl.15.25 <- quant.med(AD.MAR.cov.70[,8])
med.MAR.cov.70.AD.women.cl.25.40 <- quant.med(AD.MAR.cov.70[,9])
med.MAR.cov.70.AD.men.cl.25.40 <- quant.med(AD.MAR.cov.70[,10])
med.MAR.cov.70.AD.women.cl.40.50 <- quant.med(AD.MAR.cov.70[,11])
med.MAR.cov.70.AD.men.cl.40.50 <- quant.med(AD.MAR.cov.70[,12])
# Standard deviation
sd.MAR.cov.70.AD.women.cl.15.25 <- quant.med(AD.MAR.cov.70[,13])
sd.MAR.cov.70.AD.men.cl.15.25 <- quant.med(AD.MAR.cov.70[,14])
sd.MAR.cov.70.AD.women.cl.25.40 <- quant.med(AD.MAR.cov.70[,15])
sd.MAR.cov.70.AD.men.cl.25.40 <- quant.med(AD.MAR.cov.70[,16])
sd.MAR.cov.70.AD.women.cl.40.50 <- quant.med(AD.MAR.cov.70[,17])
sd.MAR.cov.70.AD.men.cl.40.50 <- quant.med(AD.MAR.cov.70[,18])
# Cov 75
## Vector
# Mean
vector.mean.MAR.cov.75.AD.women.cl.15.25 <- AD.MAR.cov.75[,1]
vector.mean.MAR.cov.75.AD.men.cl.15.25 <- AD.MAR.cov.75[,2]
vector.mean.MAR.cov.75.AD.women.cl.25.40 <- AD.MAR.cov.75[,3]
vector.mean.MAR.cov.75.AD.men.cl.25.40 <- AD.MAR.cov.75[,4]
vector.mean.MAR.cov.75.AD.women.cl.40.50 <- AD.MAR.cov.75[,5]
vector.mean.MAR.cov.75.AD.men.cl.40.50 <- AD.MAR.cov.75[,6]
# Median
vector.med.MAR.cov.75.AD.women.cl.15.25 <- AD.MAR.cov.75[,7]
vector.med.MAR.cov.75.AD.men.cl.15.25 <- AD.MAR.cov.75[,8]
vector.med.MAR.cov.75.AD.women.cl.25.40 <- AD.MAR.cov.75[,9]
vector.med.MAR.cov.75.AD.men.cl.25.40 <- AD.MAR.cov.75[,10]
vector.med.MAR.cov.75.AD.women.cl.40.50 <- AD.MAR.cov.75[,11]
vector.med.MAR.cov.75.AD.men.cl.40.50 <- AD.MAR.cov.75[,12]
# Standard deviation
vector.sd.MAR.cov.75.AD.women.cl.15.25 <- AD.MAR.cov.75[,13]
vector.sd.MAR.cov.75.AD.men.cl.15.25 <- AD.MAR.cov.75[,14]
vector.sd.MAR.cov.75.AD.women.cl.25.40 <- AD.MAR.cov.75[,15]
vector.sd.MAR.cov.75.AD.men.cl.25.40 <- AD.MAR.cov.75[,16]
vector.sd.MAR.cov.75.AD.women.cl.40.50 <- AD.MAR.cov.75[,17]
vector.sd.MAR.cov.75.AD.men.cl.40.50 <- AD.MAR.cov.75[,18]
## Summarised
# Mean
mean.MAR.cov.75.AD.women.cl.15.25 <- quant.med(AD.MAR.cov.75[,1])
mean.MAR.cov.75.AD.men.cl.15.25 <- quant.med(AD.MAR.cov.75[,2])
mean.MAR.cov.75.AD.women.cl.25.40 <- quant.med(AD.MAR.cov.75[,3])
mean.MAR.cov.75.AD.men.cl.25.40 <- quant.med(AD.MAR.cov.75[,4])
mean.MAR.cov.75.AD.women.cl.40.50 <- quant.med(AD.MAR.cov.75[,5])
mean.MAR.cov.75.AD.men.cl.40.50 <- quant.med(AD.MAR.cov.75[,6])
# Median
med.MAR.cov.75.AD.women.cl.15.25 <- quant.med(AD.MAR.cov.75[,7])
med.MAR.cov.75.AD.men.cl.15.25 <- quant.med(AD.MAR.cov.75[,8])
med.MAR.cov.75.AD.women.cl.25.40 <- quant.med(AD.MAR.cov.75[,9])
med.MAR.cov.75.AD.men.cl.25.40 <- quant.med(AD.MAR.cov.75[,10])
med.MAR.cov.75.AD.women.cl.40.50 <- quant.med(AD.MAR.cov.75[,11])
med.MAR.cov.75.AD.men.cl.40.50 <- quant.med(AD.MAR.cov.75[,12])
# Standard deviation
sd.MAR.cov.75.AD.women.cl.15.25 <- quant.med(AD.MAR.cov.75[,13])
sd.MAR.cov.75.AD.men.cl.15.25 <- quant.med(AD.MAR.cov.75[,14])
sd.MAR.cov.75.AD.women.cl.25.40 <- quant.med(AD.MAR.cov.75[,15])
sd.MAR.cov.75.AD.men.cl.25.40 <- quant.med(AD.MAR.cov.75[,16])
sd.MAR.cov.75.AD.women.cl.40.50 <- quant.med(AD.MAR.cov.75[,17])
sd.MAR.cov.75.AD.men.cl.40.50 <- quant.med(AD.MAR.cov.75[,18])
# Cov 80
## Vector
# Mean
vector.mean.MAR.cov.80.AD.women.cl.15.25 <- AD.MAR.cov.80[,1]
vector.mean.MAR.cov.80.AD.men.cl.15.25 <- AD.MAR.cov.80[,2]
vector.mean.MAR.cov.80.AD.women.cl.25.40 <- AD.MAR.cov.80[,3]
vector.mean.MAR.cov.80.AD.men.cl.25.40 <- AD.MAR.cov.80[,4]
vector.mean.MAR.cov.80.AD.women.cl.40.50 <- AD.MAR.cov.80[,5]
vector.mean.MAR.cov.80.AD.men.cl.40.50 <- AD.MAR.cov.80[,6]
# Median
vector.med.MAR.cov.80.AD.women.cl.15.25 <- AD.MAR.cov.80[,7]
vector.med.MAR.cov.80.AD.men.cl.15.25 <- AD.MAR.cov.80[,8]
vector.med.MAR.cov.80.AD.women.cl.25.40 <- AD.MAR.cov.80[,9]
vector.med.MAR.cov.80.AD.men.cl.25.40 <- AD.MAR.cov.80[,10]
vector.med.MAR.cov.80.AD.women.cl.40.50 <- AD.MAR.cov.80[,11]
vector.med.MAR.cov.80.AD.men.cl.40.50 <- AD.MAR.cov.80[,12]
# Standard deviation
vector.sd.MAR.cov.80.AD.women.cl.15.25 <- AD.MAR.cov.80[,13]
vector.sd.MAR.cov.80.AD.men.cl.15.25 <- AD.MAR.cov.80[,14]
vector.sd.MAR.cov.80.AD.women.cl.25.40 <- AD.MAR.cov.80[,15]
vector.sd.MAR.cov.80.AD.men.cl.25.40 <- AD.MAR.cov.80[,16]
vector.sd.MAR.cov.80.AD.women.cl.40.50 <- AD.MAR.cov.80[,17]
vector.sd.MAR.cov.80.AD.men.cl.40.50 <- AD.MAR.cov.80[,18]
## Summarised
# Mean
mean.MAR.cov.80.AD.women.cl.15.25 <- quant.med(AD.MAR.cov.80[,1])
mean.MAR.cov.80.AD.men.cl.15.25 <- quant.med(AD.MAR.cov.80[,2])
mean.MAR.cov.80.AD.women.cl.25.40 <- quant.med(AD.MAR.cov.80[,3])
mean.MAR.cov.80.AD.men.cl.25.40 <- quant.med(AD.MAR.cov.80[,4])
mean.MAR.cov.80.AD.women.cl.40.50 <- quant.med(AD.MAR.cov.80[,5])
mean.MAR.cov.80.AD.men.cl.40.50 <- quant.med(AD.MAR.cov.80[,6])
# Median
med.MAR.cov.80.AD.women.cl.15.25 <- quant.med(AD.MAR.cov.80[,7])
med.MAR.cov.80.AD.men.cl.15.25 <- quant.med(AD.MAR.cov.80[,8])
med.MAR.cov.80.AD.women.cl.25.40 <- quant.med(AD.MAR.cov.80[,9])
med.MAR.cov.80.AD.men.cl.25.40 <- quant.med(AD.MAR.cov.80[,10])
med.MAR.cov.80.AD.women.cl.40.50 <- quant.med(AD.MAR.cov.80[,11])
med.MAR.cov.80.AD.men.cl.40.50 <- quant.med(AD.MAR.cov.80[,12])
# Standard deviation
sd.MAR.cov.80.AD.women.cl.15.25 <- quant.med(AD.MAR.cov.80[,13])
sd.MAR.cov.80.AD.men.cl.15.25 <- quant.med(AD.MAR.cov.80[,14])
sd.MAR.cov.80.AD.women.cl.25.40 <- quant.med(AD.MAR.cov.80[,15])
sd.MAR.cov.80.AD.men.cl.25.40 <- quant.med(AD.MAR.cov.80[,16])
sd.MAR.cov.80.AD.women.cl.40.50 <- quant.med(AD.MAR.cov.80[,17])
sd.MAR.cov.80.AD.men.cl.40.50 <- quant.med(AD.MAR.cov.80[,18])
# Cov 85
## Vector
# Mean
vector.mean.MAR.cov.85.AD.women.cl.15.25 <- AD.MAR.cov.85[,1]
vector.mean.MAR.cov.85.AD.men.cl.15.25 <- AD.MAR.cov.85[,2]
vector.mean.MAR.cov.85.AD.women.cl.25.40 <- AD.MAR.cov.85[,3]
vector.mean.MAR.cov.85.AD.men.cl.25.40 <- AD.MAR.cov.85[,4]
vector.mean.MAR.cov.85.AD.women.cl.40.50 <- AD.MAR.cov.85[,5]
vector.mean.MAR.cov.85.AD.men.cl.40.50 <- AD.MAR.cov.85[,6]
# Median
vector.med.MAR.cov.85.AD.women.cl.15.25 <- AD.MAR.cov.85[,7]
vector.med.MAR.cov.85.AD.men.cl.15.25 <- AD.MAR.cov.85[,8]
vector.med.MAR.cov.85.AD.women.cl.25.40 <- AD.MAR.cov.85[,9]
vector.med.MAR.cov.85.AD.men.cl.25.40 <- AD.MAR.cov.85[,10]
vector.med.MAR.cov.85.AD.women.cl.40.50 <- AD.MAR.cov.85[,11]
vector.med.MAR.cov.85.AD.men.cl.40.50 <- AD.MAR.cov.85[,12]
# Standard deviation
vector.sd.MAR.cov.85.AD.women.cl.15.25 <- AD.MAR.cov.85[,13]
vector.sd.MAR.cov.85.AD.men.cl.15.25 <- AD.MAR.cov.85[,14]
vector.sd.MAR.cov.85.AD.women.cl.25.40 <- AD.MAR.cov.85[,15]
vector.sd.MAR.cov.85.AD.men.cl.25.40 <- AD.MAR.cov.85[,16]
vector.sd.MAR.cov.85.AD.women.cl.40.50 <- AD.MAR.cov.85[,17]
vector.sd.MAR.cov.85.AD.men.cl.40.50 <- AD.MAR.cov.85[,18]
## Summarised
# Mean
mean.MAR.cov.85.AD.women.cl.15.25 <- quant.med(AD.MAR.cov.85[,1])
mean.MAR.cov.85.AD.men.cl.15.25 <- quant.med(AD.MAR.cov.85[,2])
mean.MAR.cov.85.AD.women.cl.25.40 <- quant.med(AD.MAR.cov.85[,3])
mean.MAR.cov.85.AD.men.cl.25.40 <- quant.med(AD.MAR.cov.85[,4])
mean.MAR.cov.85.AD.women.cl.40.50 <- quant.med(AD.MAR.cov.85[,5])
mean.MAR.cov.85.AD.men.cl.40.50 <- quant.med(AD.MAR.cov.85[,6])
# Median
med.MAR.cov.85.AD.women.cl.15.25 <- quant.med(AD.MAR.cov.85[,7])
med.MAR.cov.85.AD.men.cl.15.25 <- quant.med(AD.MAR.cov.85[,8])
med.MAR.cov.85.AD.women.cl.25.40 <- quant.med(AD.MAR.cov.85[,9])
med.MAR.cov.85.AD.men.cl.25.40 <- quant.med(AD.MAR.cov.85[,10])
med.MAR.cov.85.AD.women.cl.40.50 <- quant.med(AD.MAR.cov.85[,11])
med.MAR.cov.85.AD.men.cl.40.50 <- quant.med(AD.MAR.cov.85[,12])
# Standard deviation
sd.MAR.cov.85.AD.women.cl.15.25 <- quant.med(AD.MAR.cov.85[,13])
sd.MAR.cov.85.AD.men.cl.15.25 <- quant.med(AD.MAR.cov.85[,14])
sd.MAR.cov.85.AD.women.cl.25.40 <- quant.med(AD.MAR.cov.85[,15])
sd.MAR.cov.85.AD.men.cl.25.40 <- quant.med(AD.MAR.cov.85[,16])
sd.MAR.cov.85.AD.women.cl.40.50 <- quant.med(AD.MAR.cov.85[,17])
sd.MAR.cov.85.AD.men.cl.40.50 <- quant.med(AD.MAR.cov.85[,18])
# Cov 90
## Vector
# Mean
vector.mean.MAR.cov.90.AD.women.cl.15.25 <- AD.MAR.cov.90[,1]
vector.mean.MAR.cov.90.AD.men.cl.15.25 <- AD.MAR.cov.90[,2]
vector.mean.MAR.cov.90.AD.women.cl.25.40 <- AD.MAR.cov.90[,3]
vector.mean.MAR.cov.90.AD.men.cl.25.40 <- AD.MAR.cov.90[,4]
vector.mean.MAR.cov.90.AD.women.cl.40.50 <- AD.MAR.cov.90[,5]
vector.mean.MAR.cov.90.AD.men.cl.40.50 <- AD.MAR.cov.90[,6]
# Median
vector.med.MAR.cov.90.AD.women.cl.15.25 <- AD.MAR.cov.90[,7]
vector.med.MAR.cov.90.AD.men.cl.15.25 <- AD.MAR.cov.90[,8]
vector.med.MAR.cov.90.AD.women.cl.25.40 <- AD.MAR.cov.90[,9]
vector.med.MAR.cov.90.AD.men.cl.25.40 <- AD.MAR.cov.90[,10]
vector.med.MAR.cov.90.AD.women.cl.40.50 <- AD.MAR.cov.90[,11]
vector.med.MAR.cov.90.AD.men.cl.40.50 <- AD.MAR.cov.90[,12]
# Standard deviation
vector.sd.MAR.cov.90.AD.women.cl.15.25 <- AD.MAR.cov.90[,13]
vector.sd.MAR.cov.90.AD.men.cl.15.25 <- AD.MAR.cov.90[,14]
vector.sd.MAR.cov.90.AD.women.cl.25.40 <- AD.MAR.cov.90[,15]
vector.sd.MAR.cov.90.AD.men.cl.25.40 <- AD.MAR.cov.90[,16]
vector.sd.MAR.cov.90.AD.women.cl.40.50 <- AD.MAR.cov.90[,17]
vector.sd.MAR.cov.90.AD.men.cl.40.50 <- AD.MAR.cov.90[,18]
## Summarised
# Mean
mean.MAR.cov.90.AD.women.cl.15.25 <- quant.med(AD.MAR.cov.90[,1])
mean.MAR.cov.90.AD.men.cl.15.25 <- quant.med(AD.MAR.cov.90[,2])
mean.MAR.cov.90.AD.women.cl.25.40 <- quant.med(AD.MAR.cov.90[,3])
mean.MAR.cov.90.AD.men.cl.25.40 <- quant.med(AD.MAR.cov.90[,4])
mean.MAR.cov.90.AD.women.cl.40.50 <- quant.med(AD.MAR.cov.90[,5])
mean.MAR.cov.90.AD.men.cl.40.50 <- quant.med(AD.MAR.cov.90[,6])
# Median
med.MAR.cov.90.AD.women.cl.15.25 <- quant.med(AD.MAR.cov.90[,7])
med.MAR.cov.90.AD.men.cl.15.25 <- quant.med(AD.MAR.cov.90[,8])
med.MAR.cov.90.AD.women.cl.25.40 <- quant.med(AD.MAR.cov.90[,9])
med.MAR.cov.90.AD.men.cl.25.40 <- quant.med(AD.MAR.cov.90[,10])
med.MAR.cov.90.AD.women.cl.40.50 <- quant.med(AD.MAR.cov.90[,11])
med.MAR.cov.90.AD.men.cl.40.50 <- quant.med(AD.MAR.cov.90[,12])
# Standard deviation
sd.MAR.cov.90.AD.women.cl.15.25 <- quant.med(AD.MAR.cov.90[,13])
sd.MAR.cov.90.AD.men.cl.15.25 <- quant.med(AD.MAR.cov.90[,14])
sd.MAR.cov.90.AD.women.cl.25.40 <- quant.med(AD.MAR.cov.90[,15])
sd.MAR.cov.90.AD.men.cl.25.40 <- quant.med(AD.MAR.cov.90[,16])
sd.MAR.cov.90.AD.women.cl.40.50 <- quant.med(AD.MAR.cov.90[,17])
sd.MAR.cov.90.AD.men.cl.40.50 <- quant.med(AD.MAR.cov.90[,18])
# Cov 95
## Vector
# Mean
vector.mean.MAR.cov.95.AD.women.cl.15.25 <- AD.MAR.cov.95[,1]
vector.mean.MAR.cov.95.AD.men.cl.15.25 <- AD.MAR.cov.95[,2]
vector.mean.MAR.cov.95.AD.women.cl.25.40 <- AD.MAR.cov.95[,3]
vector.mean.MAR.cov.95.AD.men.cl.25.40 <- AD.MAR.cov.95[,4]
vector.mean.MAR.cov.95.AD.women.cl.40.50 <- AD.MAR.cov.95[,5]
vector.mean.MAR.cov.95.AD.men.cl.40.50 <- AD.MAR.cov.95[,6]
# Median
vector.med.MAR.cov.95.AD.women.cl.15.25 <- AD.MAR.cov.95[,7]
vector.med.MAR.cov.95.AD.men.cl.15.25 <- AD.MAR.cov.95[,8]
vector.med.MAR.cov.95.AD.women.cl.25.40 <- AD.MAR.cov.95[,9]
vector.med.MAR.cov.95.AD.men.cl.25.40 <- AD.MAR.cov.95[,10]
vector.med.MAR.cov.95.AD.women.cl.40.50 <- AD.MAR.cov.95[,11]
vector.med.MAR.cov.95.AD.men.cl.40.50 <- AD.MAR.cov.95[,12]
# Standard deviation
vector.sd.MAR.cov.95.AD.women.cl.15.25 <- AD.MAR.cov.95[,13]
vector.sd.MAR.cov.95.AD.men.cl.15.25 <- AD.MAR.cov.95[,14]
vector.sd.MAR.cov.95.AD.women.cl.25.40 <- AD.MAR.cov.95[,15]
vector.sd.MAR.cov.95.AD.men.cl.25.40 <- AD.MAR.cov.95[,16]
vector.sd.MAR.cov.95.AD.women.cl.40.50 <- AD.MAR.cov.95[,17]
vector.sd.MAR.cov.95.AD.men.cl.40.50 <- AD.MAR.cov.95[,18]
## Summarised
# Mean
mean.MAR.cov.95.AD.women.cl.15.25 <- quant.med(AD.MAR.cov.95[,1])
mean.MAR.cov.95.AD.men.cl.15.25 <- quant.med(AD.MAR.cov.95[,2])
mean.MAR.cov.95.AD.women.cl.25.40 <- quant.med(AD.MAR.cov.95[,3])
mean.MAR.cov.95.AD.men.cl.25.40 <- quant.med(AD.MAR.cov.95[,4])
mean.MAR.cov.95.AD.women.cl.40.50 <- quant.med(AD.MAR.cov.95[,5])
mean.MAR.cov.95.AD.men.cl.40.50 <- quant.med(AD.MAR.cov.95[,6])
# Median
med.MAR.cov.95.AD.women.cl.15.25 <- quant.med(AD.MAR.cov.95[,7])
med.MAR.cov.95.AD.men.cl.15.25 <- quant.med(AD.MAR.cov.95[,8])
med.MAR.cov.95.AD.women.cl.25.40 <- quant.med(AD.MAR.cov.95[,9])
med.MAR.cov.95.AD.men.cl.25.40 <- quant.med(AD.MAR.cov.95[,10])
med.MAR.cov.95.AD.women.cl.40.50 <- quant.med(AD.MAR.cov.95[,11])
med.MAR.cov.95.AD.men.cl.40.50 <- quant.med(AD.MAR.cov.95[,12])
# Standard deviation
sd.MAR.cov.95.AD.women.cl.15.25 <- quant.med(AD.MAR.cov.95[,13])
sd.MAR.cov.95.AD.men.cl.15.25 <- quant.med(AD.MAR.cov.95[,14])
sd.MAR.cov.95.AD.women.cl.25.40 <- quant.med(AD.MAR.cov.95[,15])
sd.MAR.cov.95.AD.men.cl.25.40 <- quant.med(AD.MAR.cov.95[,16])
sd.MAR.cov.95.AD.women.cl.40.50 <- quant.med(AD.MAR.cov.95[,17])
sd.MAR.cov.95.AD.men.cl.40.50 <- quant.med(AD.MAR.cov.95[,18])
# Table of AD statistics inferred from transmission clusters --------
AD.stats <- matrix(c(mean.MAR.cov.35.AD.women.cl.15.25[2], mean.MAR.cov.40.AD.women.cl.15.25[2],
mean.MAR.cov.45.AD.women.cl.15.25[2], mean.MAR.cov.50.AD.women.cl.15.25[2],
mean.MAR.cov.55.AD.women.cl.15.25[2], mean.MAR.cov.60.AD.women.cl.15.25[2],
mean.MAR.cov.65.AD.women.cl.15.25[2], mean.MAR.cov.70.AD.women.cl.15.25[2],
mean.MAR.cov.75.AD.women.cl.15.25[2], mean.MAR.cov.80.AD.women.cl.15.25[2],
mean.MAR.cov.85.AD.women.cl.15.25[2], mean.MAR.cov.90.AD.women.cl.15.25[2],
mean.MAR.cov.95.AD.women.cl.15.25[2], mean.AD.num.women.true.cov.100.15.25[2],
mean.MAR.cov.35.AD.men.cl.15.25[2], mean.MAR.cov.40.AD.men.cl.15.25[2],
mean.MAR.cov.45.AD.men.cl.15.25[2], mean.MAR.cov.50.AD.men.cl.15.25[2],
mean.MAR.cov.55.AD.men.cl.15.25[2], mean.MAR.cov.60.AD.men.cl.15.25[2],
mean.MAR.cov.65.AD.men.cl.15.25[2], mean.MAR.cov.70.AD.men.cl.15.25[2],
mean.MAR.cov.75.AD.men.cl.15.25[2], mean.MAR.cov.80.AD.men.cl.15.25[2],
mean.MAR.cov.85.AD.men.cl.15.25[2], mean.MAR.cov.90.AD.men.cl.15.25[2],
mean.MAR.cov.95.AD.men.cl.15.25[2], mean.AD.num.men.true.cov.100.15.25[2],
mean.MAR.cov.35.AD.women.cl.25.40[2], mean.MAR.cov.40.AD.women.cl.25.40[2],
mean.MAR.cov.45.AD.women.cl.25.40[2], mean.MAR.cov.50.AD.women.cl.25.40[2],
mean.MAR.cov.55.AD.women.cl.25.40[2], mean.MAR.cov.60.AD.women.cl.25.40[2],
mean.MAR.cov.65.AD.women.cl.25.40[2], mean.MAR.cov.70.AD.women.cl.25.40[2],
mean.MAR.cov.75.AD.women.cl.25.40[2], mean.MAR.cov.80.AD.women.cl.25.40[2],
mean.MAR.cov.85.AD.women.cl.25.40[2], mean.MAR.cov.90.AD.women.cl.25.40[2],
mean.MAR.cov.95.AD.women.cl.25.40[2], mean.AD.num.women.true.cov.100.25.40[2],
mean.MAR.cov.35.AD.men.cl.25.40[2], mean.MAR.cov.40.AD.men.cl.25.40[2],
mean.MAR.cov.45.AD.men.cl.25.40[2], mean.MAR.cov.50.AD.men.cl.25.40[2],
mean.MAR.cov.55.AD.men.cl.25.40[2], mean.MAR.cov.60.AD.men.cl.25.40[2],
mean.MAR.cov.65.AD.men.cl.25.40[2], mean.MAR.cov.70.AD.men.cl.25.40[2],
mean.MAR.cov.75.AD.men.cl.25.40[2], mean.MAR.cov.80.AD.men.cl.25.40[2],
mean.MAR.cov.85.AD.men.cl.25.40[2], mean.MAR.cov.90.AD.men.cl.25.40[2],
mean.MAR.cov.95.AD.men.cl.25.40[2], mean.AD.num.men.true.cov.100.25.40[2],
mean.MAR.cov.35.AD.women.cl.40.50[2], mean.MAR.cov.40.AD.women.cl.40.50[2],
mean.MAR.cov.45.AD.women.cl.40.50[2], mean.MAR.cov.50.AD.women.cl.40.50[2],
mean.MAR.cov.55.AD.women.cl.40.50[2], mean.MAR.cov.60.AD.women.cl.40.50[2],
mean.MAR.cov.65.AD.women.cl.40.50[2], mean.MAR.cov.70.AD.women.cl.40.50[2],
mean.MAR.cov.75.AD.women.cl.40.50[2], mean.MAR.cov.80.AD.women.cl.40.50[2],
mean.MAR.cov.85.AD.women.cl.40.50[2], mean.MAR.cov.90.AD.women.cl.40.50[2],
mean.MAR.cov.95.AD.women.cl.40.50[2], mean.AD.num.women.true.cov.100.40.50[2],
mean.MAR.cov.35.AD.men.cl.40.50[2], mean.MAR.cov.40.AD.men.cl.40.50[2],
mean.MAR.cov.45.AD.men.cl.40.50[2], mean.MAR.cov.50.AD.men.cl.40.50[2],
mean.MAR.cov.55.AD.men.cl.40.50[2], mean.MAR.cov.60.AD.men.cl.40.50[2],
mean.MAR.cov.65.AD.men.cl.40.50[2], mean.MAR.cov.70.AD.men.cl.40.50[2],
mean.MAR.cov.75.AD.men.cl.40.50[2], mean.MAR.cov.80.AD.men.cl.40.50[2],
mean.MAR.cov.85.AD.men.cl.40.50[2], mean.MAR.cov.90.AD.men.cl.40.50[2],
mean.MAR.cov.95.AD.men.cl.40.50[2], mean.AD.num.men.true.cov.100.40.50[2],
med.MAR.cov.35.AD.women.cl.15.25[2], med.MAR.cov.40.AD.women.cl.15.25[2],
med.MAR.cov.45.AD.women.cl.15.25[2], med.MAR.cov.50.AD.women.cl.15.25[2],
med.MAR.cov.55.AD.women.cl.15.25[2], med.MAR.cov.60.AD.women.cl.15.25[2],
med.MAR.cov.65.AD.women.cl.15.25[2], med.MAR.cov.70.AD.women.cl.15.25[2],
med.MAR.cov.75.AD.women.cl.15.25[2], med.MAR.cov.80.AD.women.cl.15.25[2],
med.MAR.cov.85.AD.women.cl.15.25[2], med.MAR.cov.90.AD.women.cl.15.25[2],
med.MAR.cov.95.AD.women.cl.15.25[2], med.AD.num.women.true.cov.100.15.25[2],
med.MAR.cov.35.AD.men.cl.15.25[2], med.MAR.cov.40.AD.men.cl.15.25[2],
med.MAR.cov.45.AD.men.cl.15.25[2], med.MAR.cov.50.AD.men.cl.15.25[2],
med.MAR.cov.55.AD.men.cl.15.25[2], med.MAR.cov.60.AD.men.cl.15.25[2],
med.MAR.cov.65.AD.men.cl.15.25[2], med.MAR.cov.70.AD.men.cl.15.25[2],
med.MAR.cov.75.AD.men.cl.15.25[2], med.MAR.cov.80.AD.men.cl.15.25[2],
med.MAR.cov.85.AD.men.cl.15.25[2], med.MAR.cov.90.AD.men.cl.15.25[2],
med.MAR.cov.95.AD.men.cl.15.25[2], med.AD.num.men.true.cov.100.15.25[2],
med.MAR.cov.35.AD.women.cl.25.40[2], med.MAR.cov.40.AD.women.cl.25.40[2],
med.MAR.cov.45.AD.women.cl.25.40[2], med.MAR.cov.50.AD.women.cl.25.40[2],
med.MAR.cov.55.AD.women.cl.25.40[2], med.MAR.cov.60.AD.women.cl.25.40[2],
med.MAR.cov.65.AD.women.cl.25.40[2], med.MAR.cov.70.AD.women.cl.25.40[2],
med.MAR.cov.75.AD.women.cl.25.40[2], med.MAR.cov.80.AD.women.cl.25.40[2],
med.MAR.cov.85.AD.women.cl.25.40[2], med.MAR.cov.90.AD.women.cl.25.40[2],
med.MAR.cov.95.AD.women.cl.25.40[2], med.AD.num.women.true.cov.100.25.40[2],
med.MAR.cov.35.AD.men.cl.25.40[2], med.MAR.cov.40.AD.men.cl.25.40[2],
med.MAR.cov.45.AD.men.cl.25.40[2], med.MAR.cov.50.AD.men.cl.25.40[2],
med.MAR.cov.55.AD.men.cl.25.40[2], med.MAR.cov.60.AD.men.cl.25.40[2],
med.MAR.cov.65.AD.men.cl.25.40[2], med.MAR.cov.70.AD.men.cl.25.40[2],
med.MAR.cov.75.AD.men.cl.25.40[2], med.MAR.cov.80.AD.men.cl.25.40[2],
med.MAR.cov.85.AD.men.cl.25.40[2], med.MAR.cov.90.AD.men.cl.25.40[2],
med.MAR.cov.95.AD.men.cl.25.40[2], med.AD.num.men.true.cov.100.25.40[2],
med.MAR.cov.35.AD.women.cl.40.50[2], med.MAR.cov.40.AD.women.cl.40.50[2],
med.MAR.cov.45.AD.women.cl.40.50[2], med.MAR.cov.50.AD.women.cl.40.50[2],
med.MAR.cov.55.AD.women.cl.40.50[2], med.MAR.cov.60.AD.women.cl.40.50[2],
med.MAR.cov.65.AD.women.cl.40.50[2], med.MAR.cov.70.AD.women.cl.40.50[2],
med.MAR.cov.75.AD.women.cl.40.50[2], med.MAR.cov.80.AD.women.cl.40.50[2],
med.MAR.cov.85.AD.women.cl.40.50[2], med.MAR.cov.90.AD.women.cl.40.50[2],
med.MAR.cov.95.AD.women.cl.40.50[2], med.AD.num.women.true.cov.100.40.50[2],
med.MAR.cov.35.AD.men.cl.40.50[2], med.MAR.cov.40.AD.men.cl.40.50[2],
med.MAR.cov.45.AD.men.cl.40.50[2], med.MAR.cov.50.AD.men.cl.40.50[2],
med.MAR.cov.55.AD.men.cl.40.50[2], med.MAR.cov.60.AD.men.cl.40.50[2],
med.MAR.cov.65.AD.men.cl.40.50[2], med.MAR.cov.70.AD.men.cl.40.50[2],
med.MAR.cov.75.AD.men.cl.40.50[2], med.MAR.cov.80.AD.men.cl.40.50[2],
med.MAR.cov.85.AD.men.cl.40.50[2], med.MAR.cov.90.AD.men.cl.40.50[2],
med.MAR.cov.95.AD.men.cl.40.50[2], med.AD.num.men.true.cov.100.40.50[2],
sd.MAR.cov.35.AD.women.cl.15.25[2], sd.MAR.cov.40.AD.women.cl.15.25[2],
sd.MAR.cov.45.AD.women.cl.15.25[2], sd.MAR.cov.50.AD.women.cl.15.25[2],
sd.MAR.cov.55.AD.women.cl.15.25[2], sd.MAR.cov.60.AD.women.cl.15.25[2],
sd.MAR.cov.65.AD.women.cl.15.25[2], sd.MAR.cov.70.AD.women.cl.15.25[2],
sd.MAR.cov.75.AD.women.cl.15.25[2], sd.MAR.cov.80.AD.women.cl.15.25[2],
sd.MAR.cov.85.AD.women.cl.15.25[2], sd.MAR.cov.90.AD.women.cl.15.25[2],
sd.MAR.cov.95.AD.women.cl.15.25[2], sd.AD.num.women.true.cov.100.15.25[2],
sd.MAR.cov.35.AD.men.cl.15.25[2], sd.MAR.cov.40.AD.men.cl.15.25[2],
sd.MAR.cov.45.AD.men.cl.15.25[2], sd.MAR.cov.50.AD.men.cl.15.25[2],
sd.MAR.cov.55.AD.men.cl.15.25[2], sd.MAR.cov.60.AD.men.cl.15.25[2],
sd.MAR.cov.65.AD.men.cl.15.25[2], sd.MAR.cov.70.AD.men.cl.15.25[2],
sd.MAR.cov.75.AD.men.cl.15.25[2], sd.MAR.cov.80.AD.men.cl.15.25[2],
sd.MAR.cov.85.AD.men.cl.15.25[2], sd.MAR.cov.90.AD.men.cl.15.25[2],
sd.MAR.cov.95.AD.men.cl.15.25[2], sd.AD.num.men.true.cov.100.15.25[2],
sd.MAR.cov.35.AD.women.cl.25.40[2], sd.MAR.cov.40.AD.women.cl.25.40[2],
sd.MAR.cov.45.AD.women.cl.25.40[2], sd.MAR.cov.50.AD.women.cl.25.40[2],
sd.MAR.cov.55.AD.women.cl.25.40[2], sd.MAR.cov.60.AD.women.cl.25.40[2],
sd.MAR.cov.65.AD.women.cl.25.40[2], sd.MAR.cov.70.AD.women.cl.25.40[2],
sd.MAR.cov.75.AD.women.cl.25.40[2], sd.MAR.cov.80.AD.women.cl.25.40[2],
sd.MAR.cov.85.AD.women.cl.25.40[2], sd.MAR.cov.90.AD.women.cl.25.40[2],
sd.MAR.cov.95.AD.women.cl.25.40[2], sd.AD.num.women.true.cov.100.25.40[2],
sd.MAR.cov.35.AD.men.cl.25.40[2], sd.MAR.cov.40.AD.men.cl.25.40[2],
sd.MAR.cov.45.AD.men.cl.25.40[2], sd.MAR.cov.50.AD.men.cl.25.40[2],
sd.MAR.cov.55.AD.men.cl.25.40[2], sd.MAR.cov.60.AD.men.cl.25.40[2],
sd.MAR.cov.65.AD.men.cl.25.40[2], sd.MAR.cov.70.AD.men.cl.25.40[2],
sd.MAR.cov.75.AD.men.cl.25.40[2], sd.MAR.cov.80.AD.men.cl.25.40[2],
sd.MAR.cov.85.AD.men.cl.25.40[2], sd.MAR.cov.90.AD.men.cl.25.40[2],
sd.MAR.cov.95.AD.men.cl.25.40[2], sd.AD.num.men.true.cov.100.25.40[2],
sd.MAR.cov.35.AD.women.cl.40.50[2], sd.MAR.cov.40.AD.women.cl.40.50[2],
sd.MAR.cov.45.AD.women.cl.40.50[2], sd.MAR.cov.50.AD.women.cl.40.50[2],
sd.MAR.cov.55.AD.women.cl.40.50[2], sd.MAR.cov.60.AD.women.cl.40.50[2],
sd.MAR.cov.65.AD.women.cl.40.50[2], sd.MAR.cov.70.AD.women.cl.40.50[2],
sd.MAR.cov.75.AD.women.cl.40.50[2], sd.MAR.cov.80.AD.women.cl.40.50[2],
sd.MAR.cov.85.AD.women.cl.40.50[2], sd.MAR.cov.90.AD.women.cl.40.50[2],
sd.MAR.cov.95.AD.women.cl.40.50[2], sd.AD.num.women.true.cov.100.40.50[2],
sd.MAR.cov.35.AD.men.cl.40.50[2], sd.MAR.cov.40.AD.men.cl.40.50[2],
sd.MAR.cov.45.AD.men.cl.40.50[2], sd.MAR.cov.50.AD.men.cl.40.50[2],
sd.MAR.cov.55.AD.men.cl.40.50[2], sd.MAR.cov.60.AD.men.cl.40.50[2],
sd.MAR.cov.65.AD.men.cl.40.50[2], sd.MAR.cov.70.AD.men.cl.40.50[2],
sd.MAR.cov.75.AD.men.cl.40.50[2], sd.MAR.cov.80.AD.men.cl.40.50[2],
sd.MAR.cov.85.AD.men.cl.40.50[2], sd.MAR.cov.90.AD.men.cl.40.50[2],
sd.MAR.cov.95.AD.men.cl.40.50[2], sd.AD.num.men.true.cov.100.40.50[2]
),
ncol = 14,
byrow = TRUE)
AD.stats <- round(AD.stats, digits = 2)
colnames(AD.stats) <- c("35", "40", "45",
"50", "55", "60",
"65", "70", "75",
"80", "85", "90",
"95", "true_100")
rownames(AD.stats) <- c("mean.AD.women.cl.15.25", "mean.AD.men.cl.15.25",
"mean.AD.women.cl.25.40", "mean.AD.men.cl.25.40",
"mean.AD.women.cl.40.50", "mean.AD.men.cl.40.50",
"med.AD.women.cl.15.25", "med.AD.men.cl.15.25",
"med.AD.women.cl.25.40", "med.AD.men.cl.25.40",
"med.AD.women.cl.40.50", "med.AD.men.cl.40.50",
"sd.AD.women.cl.15.25", "sd.AD.men.cl.15.25",
"sd.AD.women.cl.25.40", "sd.AD.men.cl.25.40",
"sd.AD.women.cl.40.50", "sd.AD.men.cl.40.50")
AD.stats %>%
kable() %>%
kable_styling("striped")| 35 | 40 | 45 | 50 | 55 | 60 | 65 | 70 | 75 | 80 | 85 | 90 | 95 | true_100 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| mean.AD.women.cl.15.25 | 11.89 | 11.84 | 12.09 | 11.80 | 11.75 | 11.67 | 11.88 | 11.96 | 12.13 | 12.06 | 12.10 | 12.17 | 12.26 | 13.21 |
| mean.AD.men.cl.15.25 | 2.75 | 2.75 | 2.70 | 2.88 | 2.93 | 2.94 | 2.96 | 2.91 | 2.97 | 3.03 | 2.89 | 3.02 | 2.99 | 2.91 |
| mean.AD.women.cl.25.40 | 15.10 | 15.07 | 14.82 | 14.86 | 14.69 | 14.96 | 14.77 | 14.57 | 14.64 | 14.85 | 14.87 | 14.65 | 14.55 | 13.70 |
| mean.AD.men.cl.25.40 | 10.94 | 10.84 | 10.92 | 10.61 | 10.61 | 10.89 | 10.78 | 10.83 | 10.86 | 10.95 | 10.86 | 11.18 | 10.97 | 11.46 |
| mean.AD.women.cl.40.50 | 4.56 | 3.83 | 6.97 | 4.73 | 6.57 | 4.90 | 4.31 | 4.82 | 4.66 | 6.80 | 7.46 | 5.11 | 5.93 | 4.65 |
| mean.AD.men.cl.40.50 | 21.68 | 20.51 | 21.23 | 21.02 | 20.66 | 20.61 | 20.67 | 20.51 | 20.88 | 20.86 | 20.71 | 20.81 | 21.01 | 20.35 |
| med.AD.women.cl.15.25 | 11.57 | 11.70 | 12.07 | 11.44 | 11.57 | 11.53 | 11.55 | 11.78 | 11.91 | 11.86 | 12.21 | 12.15 | 11.99 | 13.06 |
| med.AD.men.cl.15.25 | 2.67 | 2.70 | 2.59 | 2.68 | 2.73 | 2.75 | 2.81 | 2.75 | 2.74 | 2.81 | 2.56 | 2.79 | 2.79 | 2.72 |
| med.AD.women.cl.25.40 | 15.23 | 15.20 | 14.98 | 15.12 | 14.91 | 15.19 | 15.21 | 15.01 | 15.19 | 15.20 | 15.32 | 15.11 | 14.92 | 14.57 |
| med.AD.men.cl.25.40 | 11.18 | 10.90 | 11.01 | 10.58 | 10.74 | 10.93 | 10.76 | 10.84 | 10.90 | 10.87 | 10.89 | 11.25 | 11.00 | 11.44 |
| med.AD.women.cl.40.50 | 4.56 | 3.83 | 6.88 | 5.99 | 6.57 | 3.40 | 4.62 | 4.82 | 4.75 | 7.12 | 7.46 | 5.32 | 5.93 | 4.35 |
| med.AD.men.cl.40.50 | 21.78 | 20.74 | 21.41 | 21.01 | 20.88 | 20.70 | 20.77 | 20.65 | 20.88 | 21.14 | 20.63 | 20.92 | 21.07 | 20.49 |
| sd.AD.women.cl.15.25 | 5.70 | 5.92 | 5.97 | 6.25 | 6.37 | 6.39 | 6.27 | 6.45 | 6.48 | 6.68 | 6.61 | 6.59 | 6.68 | 6.92 |
| sd.AD.men.cl.15.25 | 1.59 | 1.73 | 1.66 | 1.78 | 1.82 | 1.87 | 1.80 | 1.79 | 1.84 | 1.88 | 1.88 | 1.92 | 1.90 | 1.88 |
| sd.AD.women.cl.25.40 | 3.16 | 3.35 | 3.96 | 3.60 | 3.61 | 3.68 | 4.13 | 4.01 | 3.75 | 4.07 | 4.37 | 4.18 | 4.11 | 5.03 |
| sd.AD.men.cl.25.40 | 2.99 | 3.08 | 3.50 | 3.29 | 3.60 | 3.66 | 3.72 | 3.75 | 3.82 | 3.93 | 3.84 | 3.80 | 4.03 | 4.18 |
| sd.AD.women.cl.40.50 | 1.16 | 1.65 | 6.37 | 2.69 | 4.05 | 2.55 | 2.97 | 3.57 | 2.60 | 3.19 | 4.47 | 4.65 | 2.83 | 2.53 |
| sd.AD.men.cl.40.50 | 2.66 | 2.61 | 2.30 | 2.48 | 2.39 | 2.59 | 2.47 | 2.86 | 2.72 | 2.88 | 2.89 | 2.85 | 3.08 | 3.76 |
write.csv(AD.stats, file = "/home/david/age_mixing_patterns_phylogenetic/results/MAR_a/Table_a_16_Age_Difference_Stats_at_35_95_Coverage.csv")There is no much descrepensies between values of statistics (mean, median, and standard deviation) of true average age differences and these inferred from transmission clusters. And it seems that sequence coverage does not has an direct effect of these statistics, they look like they are stable across all sequence coverage scenarios.
One important aspect which elucidates age mixing in transmissison clusters from age difference inferred from pairings built from phylogenetic tree is: the average age difference of women between 15 and 25 years age group (~13 years with 6 years of deviation) and men between 40 and 50 years age group (~20 years with 3 years of deviation), besides for men and women in 25 and 40 years age groups (~ 14 years for women and 11 years for men with a deviation of 3-4 years for both).
This prove the existance of age mixing patterns across the transmission networks which we have seen in the true record of partnership.
# mean.women.15.25--------------------
mean.AD.women.15.25.df <- data.frame(x=c("35", "40", "45",
"50", "55", "60",
"65", "70", "75",
"80", "85", "90",
"95", "true_100"),
F = c(mean.MAR.cov.35.AD.women.cl.15.25[2], mean.MAR.cov.40.AD.women.cl.15.25[2],
mean.MAR.cov.45.AD.women.cl.15.25[2], mean.MAR.cov.50.AD.women.cl.15.25[2],
mean.MAR.cov.55.AD.women.cl.15.25[2], mean.MAR.cov.60.AD.women.cl.15.25[2],
mean.MAR.cov.65.AD.women.cl.15.25[2], mean.MAR.cov.70.AD.women.cl.15.25[2],
mean.MAR.cov.75.AD.women.cl.15.25[2], mean.MAR.cov.80.AD.women.cl.15.25[2],
mean.MAR.cov.85.AD.women.cl.15.25[2], mean.MAR.cov.90.AD.women.cl.15.25[2],
mean.MAR.cov.95.AD.women.cl.15.25[2], mean.AD.num.women.true.cov.100.15.25[2]),
L = c(mean.MAR.cov.35.AD.women.cl.15.25[1], mean.MAR.cov.40.AD.women.cl.15.25[1],
mean.MAR.cov.45.AD.women.cl.15.25[1], mean.MAR.cov.50.AD.women.cl.15.25[1],
mean.MAR.cov.55.AD.women.cl.15.25[1], mean.MAR.cov.60.AD.women.cl.15.25[1],
mean.MAR.cov.65.AD.women.cl.15.25[1], mean.MAR.cov.70.AD.women.cl.15.25[1],
mean.MAR.cov.75.AD.women.cl.15.25[1], mean.MAR.cov.80.AD.women.cl.15.25[1],
mean.MAR.cov.85.AD.women.cl.15.25[1], mean.MAR.cov.90.AD.women.cl.15.25[1],
mean.MAR.cov.95.AD.women.cl.15.25[1], mean.AD.num.women.true.cov.100.15.25[1]),
U = c(mean.MAR.cov.35.AD.women.cl.15.25[3], mean.MAR.cov.40.AD.women.cl.15.25[3],
mean.MAR.cov.45.AD.women.cl.15.25[3], mean.MAR.cov.50.AD.women.cl.15.25[3],
mean.MAR.cov.55.AD.women.cl.15.25[3], mean.MAR.cov.60.AD.women.cl.15.25[3],
mean.MAR.cov.65.AD.women.cl.15.25[3], mean.MAR.cov.70.AD.women.cl.15.25[3],
mean.MAR.cov.75.AD.women.cl.15.25[3], mean.MAR.cov.80.AD.women.cl.15.25[3],
mean.MAR.cov.85.AD.women.cl.15.25[3], mean.MAR.cov.90.AD.women.cl.15.25[3],
mean.MAR.cov.95.AD.women.cl.15.25[3], mean.AD.num.women.true.cov.100.15.25[3]))
mean.AD.women.15.25.df$parameter <- rep("mean.AD.women.15.25", nrow(mean.AD.women.15.25.df))
# mean.men.15.25--------------------
mean.AD.men.15.25.df <- data.frame(x=c("35", "40", "45",
"50", "55", "60",
"65", "70", "75",
"80", "85", "90",
"95", "true_100"),
F = c(mean.MAR.cov.35.AD.men.cl.15.25[2], mean.MAR.cov.40.AD.men.cl.15.25[2],
mean.MAR.cov.45.AD.men.cl.15.25[2], mean.MAR.cov.50.AD.men.cl.15.25[2],
mean.MAR.cov.55.AD.men.cl.15.25[2], mean.MAR.cov.60.AD.men.cl.15.25[2],
mean.MAR.cov.65.AD.men.cl.15.25[2], mean.MAR.cov.70.AD.men.cl.15.25[2],
mean.MAR.cov.75.AD.men.cl.15.25[2], mean.MAR.cov.80.AD.men.cl.15.25[2],
mean.MAR.cov.85.AD.men.cl.15.25[2], mean.MAR.cov.90.AD.men.cl.15.25[2],
mean.MAR.cov.95.AD.men.cl.15.25[2], mean.AD.num.men.true.cov.100.15.25[2]),
L = c(mean.MAR.cov.35.AD.men.cl.15.25[1], mean.MAR.cov.40.AD.men.cl.15.25[1],
mean.MAR.cov.45.AD.men.cl.15.25[1], mean.MAR.cov.50.AD.men.cl.15.25[1],
mean.MAR.cov.55.AD.men.cl.15.25[1], mean.MAR.cov.60.AD.men.cl.15.25[1],
mean.MAR.cov.65.AD.men.cl.15.25[1], mean.MAR.cov.70.AD.men.cl.15.25[1],
mean.MAR.cov.75.AD.men.cl.15.25[1], mean.MAR.cov.80.AD.men.cl.15.25[1],
mean.MAR.cov.85.AD.men.cl.15.25[1], mean.MAR.cov.90.AD.men.cl.15.25[1],
mean.MAR.cov.95.AD.men.cl.15.25[1], mean.AD.num.men.true.cov.100.15.25[1]),
U = c(mean.MAR.cov.35.AD.men.cl.15.25[3], mean.MAR.cov.40.AD.men.cl.15.25[3],
mean.MAR.cov.45.AD.men.cl.15.25[3], mean.MAR.cov.50.AD.men.cl.15.25[3],
mean.MAR.cov.55.AD.men.cl.15.25[3], mean.MAR.cov.60.AD.men.cl.15.25[3],
mean.MAR.cov.65.AD.men.cl.15.25[3], mean.MAR.cov.70.AD.men.cl.15.25[3],
mean.MAR.cov.75.AD.men.cl.15.25[3], mean.MAR.cov.80.AD.men.cl.15.25[3],
mean.MAR.cov.85.AD.men.cl.15.25[3], mean.MAR.cov.90.AD.men.cl.15.25[3],
mean.MAR.cov.95.AD.men.cl.15.25[3], mean.AD.num.men.true.cov.100.15.25[3]))
mean.AD.men.15.25.df$parameter <- rep("mean.AD.men.15.25", nrow(mean.AD.men.15.25.df))
# mean.women.25.40--------------------
mean.AD.women.25.40.df <- data.frame(x=c("35", "40", "45",
"50", "55", "60",
"65", "70", "75",
"80", "85", "90",
"95", "true_100"),
F = c(mean.MAR.cov.35.AD.women.cl.25.40[2], mean.MAR.cov.40.AD.women.cl.25.40[2],
mean.MAR.cov.45.AD.women.cl.25.40[2], mean.MAR.cov.50.AD.women.cl.25.40[2],
mean.MAR.cov.55.AD.women.cl.25.40[2], mean.MAR.cov.60.AD.women.cl.25.40[2],
mean.MAR.cov.65.AD.women.cl.25.40[2], mean.MAR.cov.70.AD.women.cl.25.40[2],
mean.MAR.cov.75.AD.women.cl.25.40[2], mean.MAR.cov.80.AD.women.cl.25.40[2],
mean.MAR.cov.85.AD.women.cl.25.40[2], mean.MAR.cov.90.AD.women.cl.25.40[2],
mean.MAR.cov.95.AD.women.cl.25.40[2], mean.AD.num.women.true.cov.100.25.40[2]),
L = c(mean.MAR.cov.35.AD.women.cl.25.40[1], mean.MAR.cov.40.AD.women.cl.25.40[1],
mean.MAR.cov.45.AD.women.cl.25.40[1], mean.MAR.cov.50.AD.women.cl.25.40[1],
mean.MAR.cov.55.AD.women.cl.25.40[1], mean.MAR.cov.60.AD.women.cl.25.40[1],
mean.MAR.cov.65.AD.women.cl.25.40[1], mean.MAR.cov.70.AD.women.cl.25.40[1],
mean.MAR.cov.75.AD.women.cl.25.40[1], mean.MAR.cov.80.AD.women.cl.25.40[1],
mean.MAR.cov.85.AD.women.cl.25.40[1], mean.MAR.cov.90.AD.women.cl.25.40[1],
mean.MAR.cov.95.AD.women.cl.25.40[1], mean.AD.num.women.true.cov.100.25.40[1]),
U = c(mean.MAR.cov.35.AD.women.cl.25.40[3], mean.MAR.cov.40.AD.women.cl.25.40[3],
mean.MAR.cov.45.AD.women.cl.25.40[3], mean.MAR.cov.50.AD.women.cl.25.40[3],
mean.MAR.cov.55.AD.women.cl.25.40[3], mean.MAR.cov.60.AD.women.cl.25.40[3],
mean.MAR.cov.65.AD.women.cl.25.40[3], mean.MAR.cov.70.AD.women.cl.25.40[3],
mean.MAR.cov.75.AD.women.cl.25.40[3], mean.MAR.cov.80.AD.women.cl.25.40[3],
mean.MAR.cov.85.AD.women.cl.25.40[3], mean.MAR.cov.90.AD.women.cl.25.40[3],
mean.MAR.cov.95.AD.women.cl.25.40[3], mean.AD.num.women.true.cov.100.25.40[3]))
mean.AD.women.25.40.df$parameter <- rep("mean.AD.women.25.40", nrow(mean.AD.women.25.40.df))
# mean.men.25.40--------------------
mean.AD.men.25.40.df <- data.frame(x=c("35", "40", "45",
"50", "55", "60",
"65", "70", "75",
"80", "85", "90",
"95", "true_100"),
F = c(mean.MAR.cov.35.AD.men.cl.25.40[2], mean.MAR.cov.40.AD.men.cl.25.40[2],
mean.MAR.cov.45.AD.men.cl.25.40[2], mean.MAR.cov.50.AD.men.cl.25.40[2],
mean.MAR.cov.55.AD.men.cl.25.40[2], mean.MAR.cov.60.AD.men.cl.25.40[2],
mean.MAR.cov.65.AD.men.cl.25.40[2], mean.MAR.cov.70.AD.men.cl.25.40[2],
mean.MAR.cov.75.AD.men.cl.25.40[2], mean.MAR.cov.80.AD.men.cl.25.40[2],
mean.MAR.cov.85.AD.men.cl.25.40[2], mean.MAR.cov.90.AD.men.cl.25.40[2],
mean.MAR.cov.95.AD.men.cl.25.40[2], mean.AD.num.men.true.cov.100.25.40[2]),
L = c(mean.MAR.cov.35.AD.men.cl.25.40[1], mean.MAR.cov.40.AD.men.cl.25.40[1],
mean.MAR.cov.45.AD.men.cl.25.40[1], mean.MAR.cov.50.AD.men.cl.25.40[1],
mean.MAR.cov.55.AD.men.cl.25.40[1], mean.MAR.cov.60.AD.men.cl.25.40[1],
mean.MAR.cov.65.AD.men.cl.25.40[1], mean.MAR.cov.70.AD.men.cl.25.40[1],
mean.MAR.cov.75.AD.men.cl.25.40[1], mean.MAR.cov.80.AD.men.cl.25.40[1],
mean.MAR.cov.85.AD.men.cl.25.40[1], mean.MAR.cov.90.AD.men.cl.25.40[1],
mean.MAR.cov.95.AD.men.cl.25.40[1], mean.AD.num.men.true.cov.100.25.40[1]),
U = c(mean.MAR.cov.35.AD.men.cl.25.40[3], mean.MAR.cov.40.AD.men.cl.25.40[3],
mean.MAR.cov.45.AD.men.cl.25.40[3], mean.MAR.cov.50.AD.men.cl.25.40[3],
mean.MAR.cov.55.AD.men.cl.25.40[3], mean.MAR.cov.60.AD.men.cl.25.40[3],
mean.MAR.cov.65.AD.men.cl.25.40[3], mean.MAR.cov.70.AD.men.cl.25.40[3],
mean.MAR.cov.75.AD.men.cl.25.40[3], mean.MAR.cov.80.AD.men.cl.25.40[3],
mean.MAR.cov.85.AD.men.cl.25.40[3], mean.MAR.cov.90.AD.men.cl.25.40[3],
mean.MAR.cov.95.AD.men.cl.25.40[3], mean.AD.num.men.true.cov.100.25.40[3]))
mean.AD.men.25.40.df$parameter <- rep("mean.AD.men.25.40", nrow(mean.AD.men.25.40.df))
# mean.women.40.50--------------------
mean.AD.women.40.50.df <- data.frame(x=c("35", "40", "45",
"50", "55", "60",
"65", "70", "75",
"80", "85", "90",
"95", "true_100"),
F = c(mean.MAR.cov.35.AD.women.cl.40.50[2], mean.MAR.cov.40.AD.women.cl.40.50[2],
mean.MAR.cov.45.AD.women.cl.40.50[2], mean.MAR.cov.50.AD.women.cl.40.50[2],
mean.MAR.cov.55.AD.women.cl.40.50[2], mean.MAR.cov.60.AD.women.cl.40.50[2],
mean.MAR.cov.65.AD.women.cl.40.50[2], mean.MAR.cov.70.AD.women.cl.40.50[2],
mean.MAR.cov.75.AD.women.cl.40.50[2], mean.MAR.cov.80.AD.women.cl.40.50[2],
mean.MAR.cov.85.AD.women.cl.40.50[2], mean.MAR.cov.90.AD.women.cl.40.50[2],
mean.MAR.cov.95.AD.women.cl.40.50[2], mean.AD.num.women.true.cov.100.40.50[2]),
L = c(mean.MAR.cov.35.AD.women.cl.40.50[1], mean.MAR.cov.40.AD.women.cl.40.50[1],
mean.MAR.cov.45.AD.women.cl.40.50[1], mean.MAR.cov.50.AD.women.cl.40.50[1],
mean.MAR.cov.55.AD.women.cl.40.50[1], mean.MAR.cov.60.AD.women.cl.40.50[1],
mean.MAR.cov.65.AD.women.cl.40.50[1], mean.MAR.cov.70.AD.women.cl.40.50[1],
mean.MAR.cov.75.AD.women.cl.40.50[1], mean.MAR.cov.80.AD.women.cl.40.50[1],
mean.MAR.cov.85.AD.women.cl.40.50[1], mean.MAR.cov.90.AD.women.cl.40.50[1],
mean.MAR.cov.95.AD.women.cl.40.50[1], mean.AD.num.women.true.cov.100.40.50[1]),
U = c(mean.MAR.cov.35.AD.women.cl.40.50[3], mean.MAR.cov.40.AD.women.cl.40.50[3],
mean.MAR.cov.45.AD.women.cl.40.50[3], mean.MAR.cov.50.AD.women.cl.40.50[3],
mean.MAR.cov.55.AD.women.cl.40.50[3], mean.MAR.cov.60.AD.women.cl.40.50[3],
mean.MAR.cov.65.AD.women.cl.40.50[3], mean.MAR.cov.70.AD.women.cl.40.50[3],
mean.MAR.cov.75.AD.women.cl.40.50[3], mean.MAR.cov.80.AD.women.cl.40.50[3],
mean.MAR.cov.85.AD.women.cl.40.50[3], mean.MAR.cov.90.AD.women.cl.40.50[3],
mean.MAR.cov.95.AD.women.cl.40.50[3], mean.AD.num.women.true.cov.100.40.50[3]))
mean.AD.women.40.50.df$parameter <- rep("mean.AD.women.40.50", nrow(mean.AD.women.40.50.df))
# mean.men.40.50--------------------
mean.AD.men.40.50.df <- data.frame(x=c("35", "40", "45",
"50", "55", "60",
"65", "70", "75",
"80", "85", "90",
"95", "true_100"),
F = c(mean.MAR.cov.35.AD.men.cl.40.50[2], mean.MAR.cov.40.AD.men.cl.40.50[2],
mean.MAR.cov.45.AD.men.cl.40.50[2], mean.MAR.cov.50.AD.men.cl.40.50[2],
mean.MAR.cov.55.AD.men.cl.40.50[2], mean.MAR.cov.60.AD.men.cl.40.50[2],
mean.MAR.cov.65.AD.men.cl.40.50[2], mean.MAR.cov.70.AD.men.cl.40.50[2],
mean.MAR.cov.75.AD.men.cl.40.50[2], mean.MAR.cov.80.AD.men.cl.40.50[2],
mean.MAR.cov.85.AD.men.cl.40.50[2], mean.MAR.cov.90.AD.men.cl.40.50[2],
mean.MAR.cov.95.AD.men.cl.40.50[2], mean.AD.num.men.true.cov.100.40.50[2]),
L = c(mean.MAR.cov.35.AD.men.cl.40.50[1], mean.MAR.cov.40.AD.men.cl.40.50[1],
mean.MAR.cov.45.AD.men.cl.40.50[1], mean.MAR.cov.50.AD.men.cl.40.50[1],
mean.MAR.cov.55.AD.men.cl.40.50[1], mean.MAR.cov.60.AD.men.cl.40.50[1],
mean.MAR.cov.65.AD.men.cl.40.50[1], mean.MAR.cov.70.AD.men.cl.40.50[1],
mean.MAR.cov.75.AD.men.cl.40.50[1], mean.MAR.cov.80.AD.men.cl.40.50[1],
mean.MAR.cov.85.AD.men.cl.40.50[1], mean.MAR.cov.90.AD.men.cl.40.50[1],
mean.MAR.cov.95.AD.men.cl.40.50[1], mean.AD.num.men.true.cov.100.40.50[1]),
U = c(mean.MAR.cov.35.AD.men.cl.40.50[3], mean.MAR.cov.40.AD.men.cl.40.50[3],
mean.MAR.cov.45.AD.men.cl.40.50[3], mean.MAR.cov.50.AD.men.cl.40.50[3],
mean.MAR.cov.55.AD.men.cl.40.50[3], mean.MAR.cov.60.AD.men.cl.40.50[3],
mean.MAR.cov.65.AD.men.cl.40.50[3], mean.MAR.cov.70.AD.men.cl.40.50[3],
mean.MAR.cov.75.AD.men.cl.40.50[3], mean.MAR.cov.80.AD.men.cl.40.50[3],
mean.MAR.cov.85.AD.men.cl.40.50[3], mean.MAR.cov.90.AD.men.cl.40.50[3],
mean.MAR.cov.95.AD.men.cl.40.50[3], mean.AD.num.men.true.cov.100.40.50[3]))
mean.AD.men.40.50.df$parameter <- rep("mean.AD.men.40.50", nrow(mean.AD.men.40.50.df))
mean.men.AD.df <- rbind(mean.AD.men.15.25.df,
mean.AD.men.25.40.df,
mean.AD.men.40.50.df)
mean.men.AD.df$gender <- rep("Males", nrow(mean.men.AD.df))
mean.women.AD.df <- rbind(mean.AD.women.15.25.df,
mean.AD.women.25.40.df,
mean.AD.women.40.50.df)
mean.women.AD.df$gender <- rep("Females", nrow(mean.women.AD.df))
df_all <- rbind(mean.men.AD.df, mean.women.AD.df)
colnames(df_all) <- c("cov", "F", "L", "U", "Parameter", "f_m")
df_all$age_grps <- c(rep("15_24", 14), rep("25_39", 14), rep("40_49", 14), rep("15_24", 14), rep("25_39", 14), rep("40_49", 14))
saveRDS(df_all, file = "/home/david/age_mixing_patterns_phylogenetic/results/MAR_a/MAR_a_11_Mean_Age_Difference_at_35_95_Coverage.RDS")
plot.mean.men.women.AD.df <- ggplot(df_all, aes(x=cov, y=F, colour=age_grps, group=Parameter)) +
geom_line(size=1) +
geom_point() +
facet_grid(.~f_m)+
# geom_errorbar(aes(ymin=L, ymax=U), width=.1) +
# ggtitle("Mean age difference in MCAR") +
xlab("Sampling Coverage (%)") + ylab("Mean Age Difference") # +
print(plot.mean.men.women.AD.df)
ggsave(filename = "Plot_a_11_Mean_Age_Difference_at_35_95_Coverage.pdf",
plot = plot.mean.men.women.AD.df,
path = "/home/david/age_mixing_patterns_phylogenetic/results/MAR_a",
width = 30, height = 15, units = "cm")# med.women.15.25--------------------
med.AD.women.15.25.df <- data.frame(x=c("35", "40", "45",
"50", "55", "60",
"65", "70", "75",
"80", "85", "90",
"95", "true_100"),
F = c(med.MAR.cov.35.AD.women.cl.15.25[2], med.MAR.cov.40.AD.women.cl.15.25[2],
med.MAR.cov.45.AD.women.cl.15.25[2], med.MAR.cov.50.AD.women.cl.15.25[2],
med.MAR.cov.55.AD.women.cl.15.25[2], med.MAR.cov.60.AD.women.cl.15.25[2],
med.MAR.cov.65.AD.women.cl.15.25[2], med.MAR.cov.70.AD.women.cl.15.25[2],
med.MAR.cov.75.AD.women.cl.15.25[2], med.MAR.cov.80.AD.women.cl.15.25[2],
med.MAR.cov.85.AD.women.cl.15.25[2], med.MAR.cov.90.AD.women.cl.15.25[2],
med.MAR.cov.95.AD.women.cl.15.25[2], med.AD.num.women.true.cov.100.15.25[2]),
L = c(med.MAR.cov.35.AD.women.cl.15.25[1], med.MAR.cov.40.AD.women.cl.15.25[1],
med.MAR.cov.45.AD.women.cl.15.25[1], med.MAR.cov.50.AD.women.cl.15.25[1],
med.MAR.cov.55.AD.women.cl.15.25[1], med.MAR.cov.60.AD.women.cl.15.25[1],
med.MAR.cov.65.AD.women.cl.15.25[1], med.MAR.cov.70.AD.women.cl.15.25[1],
med.MAR.cov.75.AD.women.cl.15.25[1], med.MAR.cov.80.AD.women.cl.15.25[1],
med.MAR.cov.85.AD.women.cl.15.25[1], med.MAR.cov.90.AD.women.cl.15.25[1],
med.MAR.cov.95.AD.women.cl.15.25[1], med.AD.num.women.true.cov.100.15.25[1]),
U = c(med.MAR.cov.35.AD.women.cl.15.25[3], med.MAR.cov.40.AD.women.cl.15.25[3],
med.MAR.cov.45.AD.women.cl.15.25[3], med.MAR.cov.50.AD.women.cl.15.25[3],
med.MAR.cov.55.AD.women.cl.15.25[3], med.MAR.cov.60.AD.women.cl.15.25[3],
med.MAR.cov.65.AD.women.cl.15.25[3], med.MAR.cov.70.AD.women.cl.15.25[3],
med.MAR.cov.75.AD.women.cl.15.25[3], med.MAR.cov.80.AD.women.cl.15.25[3],
med.MAR.cov.85.AD.women.cl.15.25[3], med.MAR.cov.90.AD.women.cl.15.25[3],
med.MAR.cov.95.AD.women.cl.15.25[3], med.AD.num.women.true.cov.100.15.25[3]))
med.AD.women.15.25.df$parameter <- rep("med.AD.women.15.25", nrow(med.AD.women.15.25.df))
# med.men.15.25--------------------
med.AD.men.15.25.df <- data.frame(x=c("35", "40", "45",
"50", "55", "60",
"65", "70", "75",
"80", "85", "90",
"95", "true_100"),
F = c(med.MAR.cov.35.AD.men.cl.15.25[2], med.MAR.cov.40.AD.men.cl.15.25[2],
med.MAR.cov.45.AD.men.cl.15.25[2], med.MAR.cov.50.AD.men.cl.15.25[2],
med.MAR.cov.55.AD.men.cl.15.25[2], med.MAR.cov.60.AD.men.cl.15.25[2],
med.MAR.cov.65.AD.men.cl.15.25[2], med.MAR.cov.70.AD.men.cl.15.25[2],
med.MAR.cov.75.AD.men.cl.15.25[2], med.MAR.cov.80.AD.men.cl.15.25[2],
med.MAR.cov.85.AD.men.cl.15.25[2], med.MAR.cov.90.AD.men.cl.15.25[2],
med.MAR.cov.95.AD.men.cl.15.25[2], med.AD.num.men.true.cov.100.15.25[2]),
L = c(med.MAR.cov.35.AD.men.cl.15.25[1], med.MAR.cov.40.AD.men.cl.15.25[1],
med.MAR.cov.45.AD.men.cl.15.25[1], med.MAR.cov.50.AD.men.cl.15.25[1],
med.MAR.cov.55.AD.men.cl.15.25[1], med.MAR.cov.60.AD.men.cl.15.25[1],
med.MAR.cov.65.AD.men.cl.15.25[1], med.MAR.cov.70.AD.men.cl.15.25[1],
med.MAR.cov.75.AD.men.cl.15.25[1], med.MAR.cov.80.AD.men.cl.15.25[1],
med.MAR.cov.85.AD.men.cl.15.25[1], med.MAR.cov.90.AD.men.cl.15.25[1],
med.MAR.cov.95.AD.men.cl.15.25[1], med.AD.num.men.true.cov.100.15.25[1]),
U = c(med.MAR.cov.35.AD.men.cl.15.25[3], med.MAR.cov.40.AD.men.cl.15.25[3],
med.MAR.cov.45.AD.men.cl.15.25[3], med.MAR.cov.50.AD.men.cl.15.25[3],
med.MAR.cov.55.AD.men.cl.15.25[3], med.MAR.cov.60.AD.men.cl.15.25[3],
med.MAR.cov.65.AD.men.cl.15.25[3], med.MAR.cov.70.AD.men.cl.15.25[3],
med.MAR.cov.75.AD.men.cl.15.25[3], med.MAR.cov.80.AD.men.cl.15.25[3],
med.MAR.cov.85.AD.men.cl.15.25[3], med.MAR.cov.90.AD.men.cl.15.25[3],
med.MAR.cov.95.AD.men.cl.15.25[3], med.AD.num.men.true.cov.100.15.25[3]))
med.AD.men.15.25.df$parameter <- rep("med.AD.men.15.25", nrow(med.AD.men.15.25.df))
# med.women.25.40--------------------
med.AD.women.25.40.df <- data.frame(x=c("35", "40", "45",
"50", "55", "60",
"65", "70", "75",
"80", "85", "90",
"95", "true_100"),
F = c(med.MAR.cov.35.AD.women.cl.25.40[2], med.MAR.cov.40.AD.women.cl.25.40[2],
med.MAR.cov.45.AD.women.cl.25.40[2], med.MAR.cov.50.AD.women.cl.25.40[2],
med.MAR.cov.55.AD.women.cl.25.40[2], med.MAR.cov.60.AD.women.cl.25.40[2],
med.MAR.cov.65.AD.women.cl.25.40[2], med.MAR.cov.70.AD.women.cl.25.40[2],
med.MAR.cov.75.AD.women.cl.25.40[2], med.MAR.cov.80.AD.women.cl.25.40[2],
med.MAR.cov.85.AD.women.cl.25.40[2], med.MAR.cov.90.AD.women.cl.25.40[2],
med.MAR.cov.95.AD.women.cl.25.40[2], med.AD.num.women.true.cov.100.25.40[2]),
L = c(med.MAR.cov.35.AD.women.cl.25.40[1], med.MAR.cov.40.AD.women.cl.25.40[1],
med.MAR.cov.45.AD.women.cl.25.40[1], med.MAR.cov.50.AD.women.cl.25.40[1],
med.MAR.cov.55.AD.women.cl.25.40[1], med.MAR.cov.60.AD.women.cl.25.40[1],
med.MAR.cov.65.AD.women.cl.25.40[1], med.MAR.cov.70.AD.women.cl.25.40[1],
med.MAR.cov.75.AD.women.cl.25.40[1], med.MAR.cov.80.AD.women.cl.25.40[1],
med.MAR.cov.85.AD.women.cl.25.40[1], med.MAR.cov.90.AD.women.cl.25.40[1],
med.MAR.cov.95.AD.women.cl.25.40[1], med.AD.num.women.true.cov.100.25.40[1]),
U = c(med.MAR.cov.35.AD.women.cl.25.40[3], med.MAR.cov.40.AD.women.cl.25.40[3],
med.MAR.cov.45.AD.women.cl.25.40[3], med.MAR.cov.50.AD.women.cl.25.40[3],
med.MAR.cov.55.AD.women.cl.25.40[3], med.MAR.cov.60.AD.women.cl.25.40[3],
med.MAR.cov.65.AD.women.cl.25.40[3], med.MAR.cov.70.AD.women.cl.25.40[3],
med.MAR.cov.75.AD.women.cl.25.40[3], med.MAR.cov.80.AD.women.cl.25.40[3],
med.MAR.cov.85.AD.women.cl.25.40[3], med.MAR.cov.90.AD.women.cl.25.40[3],
med.MAR.cov.95.AD.women.cl.25.40[3], med.AD.num.women.true.cov.100.25.40[3]))
med.AD.women.25.40.df$parameter <- rep("med.AD.women.25.40", nrow(med.AD.women.25.40.df))
# med.men.25.40--------------------
med.AD.men.25.40.df <- data.frame(x=c("35", "40", "45",
"50", "55", "60",
"65", "70", "75",
"80", "85", "90",
"95", "true_100"),
F = c(med.MAR.cov.35.AD.men.cl.25.40[2], med.MAR.cov.40.AD.men.cl.25.40[2],
med.MAR.cov.45.AD.men.cl.25.40[2], med.MAR.cov.50.AD.men.cl.25.40[2],
med.MAR.cov.55.AD.men.cl.25.40[2], med.MAR.cov.60.AD.men.cl.25.40[2],
med.MAR.cov.65.AD.men.cl.25.40[2], med.MAR.cov.70.AD.men.cl.25.40[2],
med.MAR.cov.75.AD.men.cl.25.40[2], med.MAR.cov.80.AD.men.cl.25.40[2],
med.MAR.cov.85.AD.men.cl.25.40[2], med.MAR.cov.90.AD.men.cl.25.40[2],
med.MAR.cov.95.AD.men.cl.25.40[2], med.AD.num.men.true.cov.100.25.40[2]),
L = c(med.MAR.cov.35.AD.men.cl.25.40[1], med.MAR.cov.40.AD.men.cl.25.40[1],
med.MAR.cov.45.AD.men.cl.25.40[1], med.MAR.cov.50.AD.men.cl.25.40[1],
med.MAR.cov.55.AD.men.cl.25.40[1], med.MAR.cov.60.AD.men.cl.25.40[1],
med.MAR.cov.65.AD.men.cl.25.40[1], med.MAR.cov.70.AD.men.cl.25.40[1],
med.MAR.cov.75.AD.men.cl.25.40[1], med.MAR.cov.80.AD.men.cl.25.40[1],
med.MAR.cov.85.AD.men.cl.25.40[1], med.MAR.cov.90.AD.men.cl.25.40[1],
med.MAR.cov.95.AD.men.cl.25.40[1], med.AD.num.men.true.cov.100.25.40[1]),
U = c(med.MAR.cov.35.AD.men.cl.25.40[3], med.MAR.cov.40.AD.men.cl.25.40[3],
med.MAR.cov.45.AD.men.cl.25.40[3], med.MAR.cov.50.AD.men.cl.25.40[3],
med.MAR.cov.55.AD.men.cl.25.40[3], med.MAR.cov.60.AD.men.cl.25.40[3],
med.MAR.cov.65.AD.men.cl.25.40[3], med.MAR.cov.70.AD.men.cl.25.40[3],
med.MAR.cov.75.AD.men.cl.25.40[3], med.MAR.cov.80.AD.men.cl.25.40[3],
med.MAR.cov.85.AD.men.cl.25.40[3], med.MAR.cov.90.AD.men.cl.25.40[3],
med.MAR.cov.95.AD.men.cl.25.40[3], med.AD.num.men.true.cov.100.25.40[3]))
med.AD.men.25.40.df$parameter <- rep("med.AD.men.25.40", nrow(med.AD.men.25.40.df))
# med.women.40.50--------------------
med.AD.women.40.50.df <- data.frame(x=c("35", "40", "45",
"50", "55", "60",
"65", "70", "75",
"80", "85", "90",
"95", "true_100"),
F = c(med.MAR.cov.35.AD.women.cl.40.50[2], med.MAR.cov.40.AD.women.cl.40.50[2],
med.MAR.cov.45.AD.women.cl.40.50[2], med.MAR.cov.50.AD.women.cl.40.50[2],
med.MAR.cov.55.AD.women.cl.40.50[2], med.MAR.cov.60.AD.women.cl.40.50[2],
med.MAR.cov.65.AD.women.cl.40.50[2], med.MAR.cov.70.AD.women.cl.40.50[2],
med.MAR.cov.75.AD.women.cl.40.50[2], med.MAR.cov.80.AD.women.cl.40.50[2],
med.MAR.cov.85.AD.women.cl.40.50[2], med.MAR.cov.90.AD.women.cl.40.50[2],
med.MAR.cov.95.AD.women.cl.40.50[2], med.AD.num.women.true.cov.100.40.50[2]),
L = c(med.MAR.cov.35.AD.women.cl.40.50[1], med.MAR.cov.40.AD.women.cl.40.50[1],
med.MAR.cov.45.AD.women.cl.40.50[1], med.MAR.cov.50.AD.women.cl.40.50[1],
med.MAR.cov.55.AD.women.cl.40.50[1], med.MAR.cov.60.AD.women.cl.40.50[1],
med.MAR.cov.65.AD.women.cl.40.50[1], med.MAR.cov.70.AD.women.cl.40.50[1],
med.MAR.cov.75.AD.women.cl.40.50[1], med.MAR.cov.80.AD.women.cl.40.50[1],
med.MAR.cov.85.AD.women.cl.40.50[1], med.MAR.cov.90.AD.women.cl.40.50[1],
med.MAR.cov.95.AD.women.cl.40.50[1], med.AD.num.women.true.cov.100.40.50[1]),
U = c(med.MAR.cov.35.AD.women.cl.40.50[3], med.MAR.cov.40.AD.women.cl.40.50[3],
med.MAR.cov.45.AD.women.cl.40.50[3], med.MAR.cov.50.AD.women.cl.40.50[3],
med.MAR.cov.55.AD.women.cl.40.50[3], med.MAR.cov.60.AD.women.cl.40.50[3],
med.MAR.cov.65.AD.women.cl.40.50[3], med.MAR.cov.70.AD.women.cl.40.50[3],
med.MAR.cov.75.AD.women.cl.40.50[3], med.MAR.cov.80.AD.women.cl.40.50[3],
med.MAR.cov.85.AD.women.cl.40.50[3], med.MAR.cov.90.AD.women.cl.40.50[3],
med.MAR.cov.95.AD.women.cl.40.50[3], med.AD.num.women.true.cov.100.40.50[3]))
med.AD.women.40.50.df$parameter <- rep("med.AD.women.40.50", nrow(med.AD.women.40.50.df))
# med.men.40.50--------------------
med.AD.men.40.50.df <- data.frame(x=c("35", "40", "45",
"50", "55", "60",
"65", "70", "75",
"80", "85", "90",
"95", "true_100"),
F = c(med.MAR.cov.35.AD.men.cl.40.50[2], med.MAR.cov.40.AD.men.cl.40.50[2],
med.MAR.cov.45.AD.men.cl.40.50[2], med.MAR.cov.50.AD.men.cl.40.50[2],
med.MAR.cov.55.AD.men.cl.40.50[2], med.MAR.cov.60.AD.men.cl.40.50[2],
med.MAR.cov.65.AD.men.cl.40.50[2], med.MAR.cov.70.AD.men.cl.40.50[2],
med.MAR.cov.75.AD.men.cl.40.50[2], med.MAR.cov.80.AD.men.cl.40.50[2],
med.MAR.cov.85.AD.men.cl.40.50[2], med.MAR.cov.90.AD.men.cl.40.50[2],
med.MAR.cov.95.AD.men.cl.40.50[2], med.AD.num.men.true.cov.100.40.50[2]),
L = c(med.MAR.cov.35.AD.men.cl.40.50[1], med.MAR.cov.40.AD.men.cl.40.50[1],
med.MAR.cov.45.AD.men.cl.40.50[1], med.MAR.cov.50.AD.men.cl.40.50[1],
med.MAR.cov.55.AD.men.cl.40.50[1], med.MAR.cov.60.AD.men.cl.40.50[1],
med.MAR.cov.65.AD.men.cl.40.50[1], med.MAR.cov.70.AD.men.cl.40.50[1],
med.MAR.cov.75.AD.men.cl.40.50[1], med.MAR.cov.80.AD.men.cl.40.50[1],
med.MAR.cov.85.AD.men.cl.40.50[1], med.MAR.cov.90.AD.men.cl.40.50[1],
med.MAR.cov.95.AD.men.cl.40.50[1], med.AD.num.men.true.cov.100.40.50[1]),
U = c(med.MAR.cov.35.AD.men.cl.40.50[3], med.MAR.cov.40.AD.men.cl.40.50[3],
med.MAR.cov.45.AD.men.cl.40.50[3], med.MAR.cov.50.AD.men.cl.40.50[3],
med.MAR.cov.55.AD.men.cl.40.50[3], med.MAR.cov.60.AD.men.cl.40.50[3],
med.MAR.cov.65.AD.men.cl.40.50[3], med.MAR.cov.70.AD.men.cl.40.50[3],
med.MAR.cov.75.AD.men.cl.40.50[3], med.MAR.cov.80.AD.men.cl.40.50[3],
med.MAR.cov.85.AD.men.cl.40.50[3], med.MAR.cov.90.AD.men.cl.40.50[3],
med.MAR.cov.95.AD.men.cl.40.50[3], med.AD.num.men.true.cov.100.40.50[3]))
med.AD.men.40.50.df$parameter <- rep("med.AD.men.40.50", nrow(med.AD.men.40.50.df))
med.men.AD.df <- rbind(med.AD.men.15.25.df,
med.AD.men.25.40.df,
med.AD.men.40.50.df)
med.women.AD.df <- rbind(med.AD.women.15.25.df,
med.AD.women.25.40.df,
med.AD.women.40.50.df)
med.men.AD.df$gender <- rep("Males", nrow(med.men.AD.df))
med.women.AD.df$gender <- rep("Females", nrow(med.women.AD.df))
df_all_med <- rbind(med.men.AD.df, med.women.AD.df)
colnames(df_all_med) <- c("cov", "F", "L", "U", "Parameter", "f_m")
df_all_med$age_grps <- c(rep("15_24", 14), rep("25_39", 14), rep("40_49", 14), rep("15_24", 14), rep("25_39", 14), rep("40_49", 14))
plot.med.men.women.AD.df <- ggplot(df_all_med, aes(x=cov, y=F, colour=age_grps, group=Parameter)) +
geom_line(size=1) +
geom_point() +
facet_grid(.~f_m)+
# geom_errorbar(aes(ymin=L, ymax=U), width=.1) +
# ggtitle("Mean age difference in MCAR") +
xlab("Sampling Coverage (%)") + ylab("Median Age Difference") # +
print(plot.med.men.women.AD.df)
ggsave(filename = "Plot_a_12_Median_Age_Difference_at_35_95_Coverage.pdf",
plot = plot.mean.men.women.AD.df,
path = "/home/david/age_mixing_patterns_phylogenetic/results/MAR_a",
width = 30, height = 15, units = "cm")# sd.women.15.25--------------------
sd.AD.women.15.25.df <- data.frame(x=c("35", "40", "45",
"50", "55", "60",
"65", "70", "75",
"80", "85", "90",
"95", "true_100"),
F = c(sd.MAR.cov.35.AD.women.cl.15.25[2], sd.MAR.cov.40.AD.women.cl.15.25[2],
sd.MAR.cov.45.AD.women.cl.15.25[2], sd.MAR.cov.50.AD.women.cl.15.25[2],
sd.MAR.cov.55.AD.women.cl.15.25[2], sd.MAR.cov.60.AD.women.cl.15.25[2],
sd.MAR.cov.65.AD.women.cl.15.25[2], sd.MAR.cov.70.AD.women.cl.15.25[2],
sd.MAR.cov.75.AD.women.cl.15.25[2], sd.MAR.cov.80.AD.women.cl.15.25[2],
sd.MAR.cov.85.AD.women.cl.15.25[2], sd.MAR.cov.90.AD.women.cl.15.25[2],
sd.MAR.cov.95.AD.women.cl.15.25[2], sd.AD.num.women.true.cov.100.15.25[2]),
L = c(sd.MAR.cov.35.AD.women.cl.15.25[1], sd.MAR.cov.40.AD.women.cl.15.25[1],
sd.MAR.cov.45.AD.women.cl.15.25[1], sd.MAR.cov.50.AD.women.cl.15.25[1],
sd.MAR.cov.55.AD.women.cl.15.25[1], sd.MAR.cov.60.AD.women.cl.15.25[1],
sd.MAR.cov.65.AD.women.cl.15.25[1], sd.MAR.cov.70.AD.women.cl.15.25[1],
sd.MAR.cov.75.AD.women.cl.15.25[1], sd.MAR.cov.80.AD.women.cl.15.25[1],
sd.MAR.cov.85.AD.women.cl.15.25[1], sd.MAR.cov.90.AD.women.cl.15.25[1],
sd.MAR.cov.95.AD.women.cl.15.25[1], sd.AD.num.women.true.cov.100.15.25[1]),
U = c(sd.MAR.cov.35.AD.women.cl.15.25[3], sd.MAR.cov.40.AD.women.cl.15.25[3],
sd.MAR.cov.45.AD.women.cl.15.25[3], sd.MAR.cov.50.AD.women.cl.15.25[3],
sd.MAR.cov.55.AD.women.cl.15.25[3], sd.MAR.cov.60.AD.women.cl.15.25[3],
sd.MAR.cov.65.AD.women.cl.15.25[3], sd.MAR.cov.70.AD.women.cl.15.25[3],
sd.MAR.cov.75.AD.women.cl.15.25[3], sd.MAR.cov.80.AD.women.cl.15.25[3],
sd.MAR.cov.85.AD.women.cl.15.25[3], sd.MAR.cov.90.AD.women.cl.15.25[3],
sd.MAR.cov.95.AD.women.cl.15.25[3], sd.AD.num.women.true.cov.100.15.25[3]))
sd.AD.women.15.25.df$parameter <- rep("sd.AD.women.15.25", nrow(sd.AD.women.15.25.df))
# sd.men.15.25--------------------
sd.AD.men.15.25.df <- data.frame(x=c("35", "40", "45",
"50", "55", "60",
"65", "70", "75",
"80", "85", "90",
"95", "true_100"),
F = c(sd.MAR.cov.35.AD.men.cl.15.25[2], sd.MAR.cov.40.AD.men.cl.15.25[2],
sd.MAR.cov.45.AD.men.cl.15.25[2], sd.MAR.cov.50.AD.men.cl.15.25[2],
sd.MAR.cov.55.AD.men.cl.15.25[2], sd.MAR.cov.60.AD.men.cl.15.25[2],
sd.MAR.cov.65.AD.men.cl.15.25[2], sd.MAR.cov.70.AD.men.cl.15.25[2],
sd.MAR.cov.75.AD.men.cl.15.25[2], sd.MAR.cov.80.AD.men.cl.15.25[2],
sd.MAR.cov.85.AD.men.cl.15.25[2], sd.MAR.cov.90.AD.men.cl.15.25[2],
sd.MAR.cov.95.AD.men.cl.15.25[2], sd.AD.num.men.true.cov.100.15.25[2]),
L = c(sd.MAR.cov.35.AD.men.cl.15.25[1], sd.MAR.cov.40.AD.men.cl.15.25[1],
sd.MAR.cov.45.AD.men.cl.15.25[1], sd.MAR.cov.50.AD.men.cl.15.25[1],
sd.MAR.cov.55.AD.men.cl.15.25[1], sd.MAR.cov.60.AD.men.cl.15.25[1],
sd.MAR.cov.65.AD.men.cl.15.25[1], sd.MAR.cov.70.AD.men.cl.15.25[1],
sd.MAR.cov.75.AD.men.cl.15.25[1], sd.MAR.cov.80.AD.men.cl.15.25[1],
sd.MAR.cov.85.AD.men.cl.15.25[1], sd.MAR.cov.90.AD.men.cl.15.25[1],
sd.MAR.cov.95.AD.men.cl.15.25[1], sd.AD.num.men.true.cov.100.15.25[1]),
U = c(sd.MAR.cov.35.AD.men.cl.15.25[3], sd.MAR.cov.40.AD.men.cl.15.25[3],
sd.MAR.cov.45.AD.men.cl.15.25[3], sd.MAR.cov.50.AD.men.cl.15.25[3],
sd.MAR.cov.55.AD.men.cl.15.25[3], sd.MAR.cov.60.AD.men.cl.15.25[3],
sd.MAR.cov.65.AD.men.cl.15.25[3], sd.MAR.cov.70.AD.men.cl.15.25[3],
sd.MAR.cov.75.AD.men.cl.15.25[3], sd.MAR.cov.80.AD.men.cl.15.25[3],
sd.MAR.cov.85.AD.men.cl.15.25[3], sd.MAR.cov.90.AD.men.cl.15.25[3],
sd.MAR.cov.95.AD.men.cl.15.25[3], sd.AD.num.men.true.cov.100.15.25[3]))
sd.AD.men.15.25.df$parameter <- rep("sd.AD.men.15.25", nrow(sd.AD.men.15.25.df))
# sd.women.25.40--------------------
sd.AD.women.25.40.df <- data.frame(x=c("35", "40", "45",
"50", "55", "60",
"65", "70", "75",
"80", "85", "90",
"95", "true_100"),
F = c(sd.MAR.cov.35.AD.women.cl.25.40[2], sd.MAR.cov.40.AD.women.cl.25.40[2],
sd.MAR.cov.45.AD.women.cl.25.40[2], sd.MAR.cov.50.AD.women.cl.25.40[2],
sd.MAR.cov.55.AD.women.cl.25.40[2], sd.MAR.cov.60.AD.women.cl.25.40[2],
sd.MAR.cov.65.AD.women.cl.25.40[2], sd.MAR.cov.70.AD.women.cl.25.40[2],
sd.MAR.cov.75.AD.women.cl.25.40[2], sd.MAR.cov.80.AD.women.cl.25.40[2],
sd.MAR.cov.85.AD.women.cl.25.40[2], sd.MAR.cov.90.AD.women.cl.25.40[2],
sd.MAR.cov.95.AD.women.cl.25.40[2], sd.AD.num.women.true.cov.100.25.40[2]),
L = c(sd.MAR.cov.35.AD.women.cl.25.40[1], sd.MAR.cov.40.AD.women.cl.25.40[1],
sd.MAR.cov.45.AD.women.cl.25.40[1], sd.MAR.cov.50.AD.women.cl.25.40[1],
sd.MAR.cov.55.AD.women.cl.25.40[1], sd.MAR.cov.60.AD.women.cl.25.40[1],
sd.MAR.cov.65.AD.women.cl.25.40[1], sd.MAR.cov.70.AD.women.cl.25.40[1],
sd.MAR.cov.75.AD.women.cl.25.40[1], sd.MAR.cov.80.AD.women.cl.25.40[1],
sd.MAR.cov.85.AD.women.cl.25.40[1], sd.MAR.cov.90.AD.women.cl.25.40[1],
sd.MAR.cov.95.AD.women.cl.25.40[1], sd.AD.num.women.true.cov.100.25.40[1]),
U = c(sd.MAR.cov.35.AD.women.cl.25.40[3], sd.MAR.cov.40.AD.women.cl.25.40[3],
sd.MAR.cov.45.AD.women.cl.25.40[3], sd.MAR.cov.50.AD.women.cl.25.40[3],
sd.MAR.cov.55.AD.women.cl.25.40[3], sd.MAR.cov.60.AD.women.cl.25.40[3],
sd.MAR.cov.65.AD.women.cl.25.40[3], sd.MAR.cov.70.AD.women.cl.25.40[3],
sd.MAR.cov.75.AD.women.cl.25.40[3], sd.MAR.cov.80.AD.women.cl.25.40[3],
sd.MAR.cov.85.AD.women.cl.25.40[3], sd.MAR.cov.90.AD.women.cl.25.40[3],
sd.MAR.cov.95.AD.women.cl.25.40[3], sd.AD.num.women.true.cov.100.25.40[3]))
sd.AD.women.25.40.df$parameter <- rep("sd.AD.women.25.40", nrow(sd.AD.women.25.40.df))
# sd.men.25.40--------------------
sd.AD.men.25.40.df <- data.frame(x=c("35", "40", "45",
"50", "55", "60",
"65", "70", "75",
"80", "85", "90",
"95", "true_100"),
F = c(sd.MAR.cov.35.AD.men.cl.25.40[2], sd.MAR.cov.40.AD.men.cl.25.40[2],
sd.MAR.cov.45.AD.men.cl.25.40[2], sd.MAR.cov.50.AD.men.cl.25.40[2],
sd.MAR.cov.55.AD.men.cl.25.40[2], sd.MAR.cov.60.AD.men.cl.25.40[2],
sd.MAR.cov.65.AD.men.cl.25.40[2], sd.MAR.cov.70.AD.men.cl.25.40[2],
sd.MAR.cov.75.AD.men.cl.25.40[2], sd.MAR.cov.80.AD.men.cl.25.40[2],
sd.MAR.cov.85.AD.men.cl.25.40[2], sd.MAR.cov.90.AD.men.cl.25.40[2],
sd.MAR.cov.95.AD.men.cl.25.40[2], sd.AD.num.men.true.cov.100.25.40[2]),
L = c(sd.MAR.cov.35.AD.men.cl.25.40[1], sd.MAR.cov.40.AD.men.cl.25.40[1],
sd.MAR.cov.45.AD.men.cl.25.40[1], sd.MAR.cov.50.AD.men.cl.25.40[1],
sd.MAR.cov.55.AD.men.cl.25.40[1], sd.MAR.cov.60.AD.men.cl.25.40[1],
sd.MAR.cov.65.AD.men.cl.25.40[1], sd.MAR.cov.70.AD.men.cl.25.40[1],
sd.MAR.cov.75.AD.men.cl.25.40[1], sd.MAR.cov.80.AD.men.cl.25.40[1],
sd.MAR.cov.85.AD.men.cl.25.40[1], sd.MAR.cov.90.AD.men.cl.25.40[1],
sd.MAR.cov.95.AD.men.cl.25.40[1], sd.AD.num.men.true.cov.100.25.40[1]),
U = c(sd.MAR.cov.35.AD.men.cl.25.40[3], sd.MAR.cov.40.AD.men.cl.25.40[3],
sd.MAR.cov.45.AD.men.cl.25.40[3], sd.MAR.cov.50.AD.men.cl.25.40[3],
sd.MAR.cov.55.AD.men.cl.25.40[3], sd.MAR.cov.60.AD.men.cl.25.40[3],
sd.MAR.cov.65.AD.men.cl.25.40[3], sd.MAR.cov.70.AD.men.cl.25.40[3],
sd.MAR.cov.75.AD.men.cl.25.40[3], sd.MAR.cov.80.AD.men.cl.25.40[3],
sd.MAR.cov.85.AD.men.cl.25.40[3], sd.MAR.cov.90.AD.men.cl.25.40[3],
sd.MAR.cov.95.AD.men.cl.25.40[3], sd.AD.num.men.true.cov.100.25.40[3]))
sd.AD.men.25.40.df$parameter <- rep("sd.AD.men.25.40", nrow(sd.AD.men.25.40.df))
# sd.women.40.50--------------------
sd.AD.women.40.50.df <- data.frame(x=c("35", "40", "45",
"50", "55", "60",
"65", "70", "75",
"80", "85", "90",
"95", "true_100"),
F = c(sd.MAR.cov.35.AD.women.cl.40.50[2], sd.MAR.cov.40.AD.women.cl.40.50[2],
sd.MAR.cov.45.AD.women.cl.40.50[2], sd.MAR.cov.50.AD.women.cl.40.50[2],
sd.MAR.cov.55.AD.women.cl.40.50[2], sd.MAR.cov.60.AD.women.cl.40.50[2],
sd.MAR.cov.65.AD.women.cl.40.50[2], sd.MAR.cov.70.AD.women.cl.40.50[2],
sd.MAR.cov.75.AD.women.cl.40.50[2], sd.MAR.cov.80.AD.women.cl.40.50[2],
sd.MAR.cov.85.AD.women.cl.40.50[2], sd.MAR.cov.90.AD.women.cl.40.50[2],
sd.MAR.cov.95.AD.women.cl.40.50[2], sd.AD.num.women.true.cov.100.40.50[2]),
L = c(sd.MAR.cov.35.AD.women.cl.40.50[1], sd.MAR.cov.40.AD.women.cl.40.50[1],
sd.MAR.cov.45.AD.women.cl.40.50[1], sd.MAR.cov.50.AD.women.cl.40.50[1],
sd.MAR.cov.55.AD.women.cl.40.50[1], sd.MAR.cov.60.AD.women.cl.40.50[1],
sd.MAR.cov.65.AD.women.cl.40.50[1], sd.MAR.cov.70.AD.women.cl.40.50[1],
sd.MAR.cov.75.AD.women.cl.40.50[1], sd.MAR.cov.80.AD.women.cl.40.50[1],
sd.MAR.cov.85.AD.women.cl.40.50[1], sd.MAR.cov.90.AD.women.cl.40.50[1],
sd.MAR.cov.95.AD.women.cl.40.50[1], sd.AD.num.women.true.cov.100.40.50[1]),
U = c(sd.MAR.cov.35.AD.women.cl.40.50[3], sd.MAR.cov.40.AD.women.cl.40.50[3],
sd.MAR.cov.45.AD.women.cl.40.50[3], sd.MAR.cov.50.AD.women.cl.40.50[3],
sd.MAR.cov.55.AD.women.cl.40.50[3], sd.MAR.cov.60.AD.women.cl.40.50[3],
sd.MAR.cov.65.AD.women.cl.40.50[3], sd.MAR.cov.70.AD.women.cl.40.50[3],
sd.MAR.cov.75.AD.women.cl.40.50[3], sd.MAR.cov.80.AD.women.cl.40.50[3],
sd.MAR.cov.85.AD.women.cl.40.50[3], sd.MAR.cov.90.AD.women.cl.40.50[3],
sd.MAR.cov.95.AD.women.cl.40.50[3], sd.AD.num.women.true.cov.100.40.50[3]))
sd.AD.women.40.50.df$parameter <- rep("sd.AD.women.40.50", nrow(sd.AD.women.40.50.df))
# sd.men.40.50--------------------
sd.AD.men.40.50.df <- data.frame(x=c("35", "40", "45",
"50", "55", "60",
"65", "70", "75",
"80", "85", "90",
"95", "true_100"),
F = c(sd.MAR.cov.35.AD.men.cl.40.50[2], sd.MAR.cov.40.AD.men.cl.40.50[2],
sd.MAR.cov.45.AD.men.cl.40.50[2], sd.MAR.cov.50.AD.men.cl.40.50[2],
sd.MAR.cov.55.AD.men.cl.40.50[2], sd.MAR.cov.60.AD.men.cl.40.50[2],
sd.MAR.cov.65.AD.men.cl.40.50[2], sd.MAR.cov.70.AD.men.cl.40.50[2],
sd.MAR.cov.75.AD.men.cl.40.50[2], sd.MAR.cov.80.AD.men.cl.40.50[2],
sd.MAR.cov.85.AD.men.cl.40.50[2], sd.MAR.cov.90.AD.men.cl.40.50[2],
sd.MAR.cov.95.AD.men.cl.40.50[2], sd.AD.num.men.true.cov.100.40.50[2]),
L = c(sd.MAR.cov.35.AD.men.cl.40.50[1], sd.MAR.cov.40.AD.men.cl.40.50[1],
sd.MAR.cov.45.AD.men.cl.40.50[1], sd.MAR.cov.50.AD.men.cl.40.50[1],
sd.MAR.cov.55.AD.men.cl.40.50[1], sd.MAR.cov.60.AD.men.cl.40.50[1],
sd.MAR.cov.65.AD.men.cl.40.50[1], sd.MAR.cov.70.AD.men.cl.40.50[1],
sd.MAR.cov.75.AD.men.cl.40.50[1], sd.MAR.cov.80.AD.men.cl.40.50[1],
sd.MAR.cov.85.AD.men.cl.40.50[1], sd.MAR.cov.90.AD.men.cl.40.50[1],
sd.MAR.cov.95.AD.men.cl.40.50[1], sd.AD.num.men.true.cov.100.40.50[1]),
U = c(sd.MAR.cov.35.AD.men.cl.40.50[3], sd.MAR.cov.40.AD.men.cl.40.50[3],
sd.MAR.cov.45.AD.men.cl.40.50[3], sd.MAR.cov.50.AD.men.cl.40.50[3],
sd.MAR.cov.55.AD.men.cl.40.50[3], sd.MAR.cov.60.AD.men.cl.40.50[3],
sd.MAR.cov.65.AD.men.cl.40.50[3], sd.MAR.cov.70.AD.men.cl.40.50[3],
sd.MAR.cov.75.AD.men.cl.40.50[3], sd.MAR.cov.80.AD.men.cl.40.50[3],
sd.MAR.cov.85.AD.men.cl.40.50[3], sd.MAR.cov.90.AD.men.cl.40.50[3],
sd.MAR.cov.95.AD.men.cl.40.50[3], sd.AD.num.men.true.cov.100.40.50[3]))
sd.AD.men.40.50.df$parameter <- rep("sd.AD.men.40.50", nrow(sd.AD.men.40.50.df))
sd.men.AD.df <- rbind(sd.AD.men.15.25.df,
sd.AD.men.25.40.df,
sd.AD.men.40.50.df)
sd.women.AD.df <- rbind(sd.AD.women.15.25.df,
sd.AD.women.25.40.df,
sd.AD.women.40.50.df)
#
sd.men.AD.df$gender <- rep("Males", nrow(sd.men.AD.df))
sd.women.AD.df$gender <- rep("Females", nrow(sd.women.AD.df))
df_all_sd <- rbind(sd.men.AD.df, sd.women.AD.df)
colnames(df_all_sd) <- c("cov", "F", "L", "U", "Parameter", "f_m")
df_all_sd$age_grps <- c(rep("15_24", 14), rep("25_39", 14), rep("40_49", 14), rep("15_24", 14), rep("25_39", 14), rep("40_49", 14))
saveRDS(df_all_sd, file = "/home/david/age_mixing_patterns_phylogenetic/results/MAR_a/MAR_a_13_Standard_Deviation_Age_Difference_at_35_95_Coverage.RDS")
plot.sd.men.women.AD.df <- ggplot(df_all_sd, aes(x=cov, y=F, colour=age_grps, group=Parameter)) +
geom_line(size=1)+
geom_point() +
facet_grid(.~f_m)+
# geom_errorbar(aes(ymin=L, ymax=U), width=.1) +
# ggtitle("Mean age difference in MCAR") +
xlab("Sampling Coverage (%)") + ylab("Standard Deviation of Age Difference") # +
print(plot.sd.men.women.AD.df)
ggsave(filename = "Plot_a_13_Standard_Deviation_Age_Difference_at_35_95_Coverage.pdf",
plot = plot.sd.men.women.AD.df,
path = "/home/david/age_mixing_patterns_phylogenetic/results/MAR_a",
width = 30, height = 15, units = "cm")
#
pdf("/home/david/age_mixing_patterns_phylogenetic/results/MAR_a/Plot_a_14_Mean_SD_Age_Difference_at_35_95_Coverage.pdf",
width=15, height=15)
gridExtra::grid.arrange(plot.mean.men.women.AD.df, plot.sd.men.women.AD.df)
dev.off()## png
## 25.3 Goodness of fit of statistics of age difference in pairings from transmission clusters
We compute the Root Mean Squared Error (RMSE) of the mean/median/standard deviation of the average age difference in pairings per each sampling scenario:
\[\sqrt{mean[(V_{true_{100}} – V_{cov})^2]}\]
where \(V_{true_{100}}\) is a vector of true values of mean/median/standard deviation of the average age difference in pairings at 100%, and \(V_{cov}\) the average age difference in pairings values at a given sampling scenario.
# Cov 35
# 15.25
# Mean
error.infer.clust.cov.100.men.15.25.cov.35.mean <- as.numeric(vector.mean.AD.num.men.true.cov.100.15.25) - as.numeric(vector.mean.MAR.cov.35.AD.men.cl.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.cov.35.mean <- RMSE(error.infer.clust.cov.100.men.15.25.cov.35.mean)
MAE.error.infer.clust.cov.100.men.15.25.cov.35.mean <- MAE(error.infer.clust.cov.100.men.15.25.cov.35.mean)
ARMSE.error.infer.clust.cov.100.men.15.25.cov.35 <- ARMSE(v1=vector.mean.AD.num.men.true.cov.100.15.25, v2=vector.mean.MAR.cov.35.AD.men.cl.15.25)
MRE.error.infer.clust.cov.100.men.15.25.cov.35.mean <- MRE(error.infer.clust.cov.100.men.15.25.cov.35.mean)
error.infer.clust.cov.100.women.15.25.cov.35.mean <- as.numeric(vector.mean.AD.num.women.true.cov.100.15.25) - as.numeric(vector.mean.MAR.cov.35.AD.women.cl.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.cov.35.mean <- RMSE(error.infer.clust.cov.100.women.15.25.cov.35.mean)
MAE.error.infer.clust.cov.100.women.15.25.cov.35.mean <- MAE(error.infer.clust.cov.100.women.15.25.cov.35.mean)
ARMSE.error.infer.clust.cov.100.women.15.25.cov.35.mean <- ARMSE(v1=vector.mean.AD.num.women.true.cov.100.15.25, v2=vector.mean.MAR.cov.35.AD.women.cl.15.25)
MRE.error.infer.clust.cov.100.women.15.25.cov.35.mean <- MRE(error.infer.clust.cov.100.women.15.25.cov.35.mean)
# Median
error.infer.clust.cov.100.men.15.25.cov.35.med <- as.numeric(vector.med.AD.num.men.true.cov.100.15.25) - as.numeric(vector.med.MAR.cov.35.AD.men.cl.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.cov.35.med <- RMSE(error.infer.clust.cov.100.men.15.25.cov.35.med)
MAE.error.infer.clust.cov.100.men.15.25.cov.35.med <- MAE(error.infer.clust.cov.100.men.15.25.cov.35.med)
ARMSE.error.infer.clust.cov.100.men.15.25.cov.35 <- ARMSE(v1=vector.med.AD.num.men.true.cov.100.15.25, v2=vector.med.MAR.cov.35.AD.men.cl.15.25)
MRE.error.infer.clust.cov.100.men.15.25.cov.35.med <- MRE(error.infer.clust.cov.100.men.15.25.cov.35.med)
error.infer.clust.cov.100.women.15.25.cov.35.med <- as.numeric(vector.med.AD.num.women.true.cov.100.15.25) - as.numeric(vector.med.MAR.cov.35.AD.women.cl.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.cov.35.med <- RMSE(error.infer.clust.cov.100.women.15.25.cov.35.med)
MAE.error.infer.clust.cov.100.women.15.25.cov.35.med <- MAE(error.infer.clust.cov.100.women.15.25.cov.35.med)
ARMSE.error.infer.clust.cov.100.women.15.25.cov.35.med <- ARMSE(v1=vector.med.AD.num.women.true.cov.100.15.25, v2=vector.med.MAR.cov.35.AD.women.cl.15.25)
MRE.error.infer.clust.cov.100.women.15.25.cov.35.med <- MRE(error.infer.clust.cov.100.women.15.25.cov.35.med)
# Standard deviation
error.infer.clust.cov.100.men.15.25.cov.35.sd <- as.numeric(vector.sd.AD.num.men.true.cov.100.15.25) - as.numeric(vector.sd.MAR.cov.35.AD.men.cl.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.cov.35.sd <- RMSE(error.infer.clust.cov.100.men.15.25.cov.35.sd)
MAE.error.infer.clust.cov.100.men.15.25.cov.35.sd <- MAE(error.infer.clust.cov.100.men.15.25.cov.35.sd)
ARMSE.error.infer.clust.cov.100.men.15.25.cov.35 <- ARMSE(v1=vector.sd.AD.num.men.true.cov.100.15.25, v2=vector.sd.MAR.cov.35.AD.men.cl.15.25)
MRE.error.infer.clust.cov.100.men.15.25.cov.35.sd <- MRE(error.infer.clust.cov.100.men.15.25.cov.35.sd)
error.infer.clust.cov.100.women.15.25.cov.35.sd <- as.numeric(vector.sd.AD.num.women.true.cov.100.15.25) - as.numeric(vector.sd.MAR.cov.35.AD.women.cl.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.cov.35.sd <- RMSE(error.infer.clust.cov.100.women.15.25.cov.35.sd)
MAE.error.infer.clust.cov.100.women.15.25.cov.35.sd <- MAE(error.infer.clust.cov.100.women.15.25.cov.35.sd)
ARMSE.error.infer.clust.cov.100.women.15.25.cov.35.sd <- ARMSE(v1=vector.sd.AD.num.women.true.cov.100.15.25, v2=vector.sd.MAR.cov.35.AD.women.cl.15.25)
MRE.error.infer.clust.cov.100.women.15.25.cov.35.sd <- MRE(error.infer.clust.cov.100.women.15.25.cov.35.sd)
# 25.40
# Mean
error.infer.clust.cov.100.men.25.40.cov.35.mean <- as.numeric(vector.mean.AD.num.men.true.cov.100.25.40) - as.numeric(vector.mean.MAR.cov.35.AD.men.cl.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.cov.35.mean <- RMSE(error.infer.clust.cov.100.men.25.40.cov.35.mean)
MAE.error.infer.clust.cov.100.men.25.40.cov.35.mean <- MAE(error.infer.clust.cov.100.men.25.40.cov.35.mean)
ARMSE.error.infer.clust.cov.100.men.25.40.cov.35 <- ARMSE(v1=vector.mean.AD.num.men.true.cov.100.25.40, v2=vector.mean.MAR.cov.35.AD.men.cl.25.40)
MRE.error.infer.clust.cov.100.men.25.40.cov.35.mean <- MRE(error.infer.clust.cov.100.men.25.40.cov.35.mean)
error.infer.clust.cov.100.women.25.40.cov.35.mean <- as.numeric(vector.mean.AD.num.women.true.cov.100.25.40) - as.numeric(vector.mean.MAR.cov.35.AD.women.cl.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.cov.35.mean <- RMSE(error.infer.clust.cov.100.women.25.40.cov.35.mean)
MAE.error.infer.clust.cov.100.women.25.40.cov.35.mean <- MAE(error.infer.clust.cov.100.women.25.40.cov.35.mean)
ARMSE.error.infer.clust.cov.100.women.25.40.cov.35.mean <- ARMSE(v1=vector.mean.AD.num.women.true.cov.100.25.40, v2=vector.mean.MAR.cov.35.AD.women.cl.25.40)
MRE.error.infer.clust.cov.100.women.25.40.cov.35.mean <- MRE(error.infer.clust.cov.100.women.25.40.cov.35.mean)
# Median
error.infer.clust.cov.100.men.25.40.cov.35.med <- as.numeric(vector.med.AD.num.men.true.cov.100.25.40) - as.numeric(vector.med.MAR.cov.35.AD.men.cl.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.cov.35.med <- RMSE(error.infer.clust.cov.100.men.25.40.cov.35.med)
MAE.error.infer.clust.cov.100.men.25.40.cov.35.med <- MAE(error.infer.clust.cov.100.men.25.40.cov.35.med)
ARMSE.error.infer.clust.cov.100.men.25.40.cov.35 <- ARMSE(v1=vector.med.AD.num.men.true.cov.100.25.40, v2=vector.med.MAR.cov.35.AD.men.cl.25.40)
MRE.error.infer.clust.cov.100.men.25.40.cov.35.med <- MRE(error.infer.clust.cov.100.men.25.40.cov.35.med)
error.infer.clust.cov.100.women.25.40.cov.35.med <- as.numeric(vector.med.AD.num.women.true.cov.100.25.40) - as.numeric(vector.med.MAR.cov.35.AD.women.cl.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.cov.35.med <- RMSE(error.infer.clust.cov.100.women.25.40.cov.35.med)
MAE.error.infer.clust.cov.100.women.25.40.cov.35.med <- MAE(error.infer.clust.cov.100.women.25.40.cov.35.med)
ARMSE.error.infer.clust.cov.100.women.25.40.cov.35.med <- ARMSE(v1=vector.med.AD.num.women.true.cov.100.25.40, v2=vector.med.MAR.cov.35.AD.women.cl.25.40)
MRE.error.infer.clust.cov.100.women.25.40.cov.35.med <- MRE(error.infer.clust.cov.100.women.25.40.cov.35.med)
# Standard deviation
error.infer.clust.cov.100.men.25.40.cov.35.sd <- as.numeric(vector.sd.AD.num.men.true.cov.100.25.40) - as.numeric(vector.sd.MAR.cov.35.AD.men.cl.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.cov.35.sd <- RMSE(error.infer.clust.cov.100.men.25.40.cov.35.sd)
MAE.error.infer.clust.cov.100.men.25.40.cov.35.sd <- MAE(error.infer.clust.cov.100.men.25.40.cov.35.sd)
ARMSE.error.infer.clust.cov.100.men.25.40.cov.35 <- ARMSE(v1=vector.sd.AD.num.men.true.cov.100.25.40, v2=vector.sd.MAR.cov.35.AD.men.cl.25.40)
MRE.error.infer.clust.cov.100.men.25.40.cov.35.sd <- MRE(error.infer.clust.cov.100.men.25.40.cov.35.sd)
error.infer.clust.cov.100.women.25.40.cov.35.sd <- as.numeric(vector.sd.AD.num.women.true.cov.100.25.40) - as.numeric(vector.sd.MAR.cov.35.AD.women.cl.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.cov.35.sd <- RMSE(error.infer.clust.cov.100.women.25.40.cov.35.sd)
MAE.error.infer.clust.cov.100.women.25.40.cov.35.sd <- MAE(error.infer.clust.cov.100.women.25.40.cov.35.sd)
ARMSE.error.infer.clust.cov.100.women.25.40.cov.35.sd <- ARMSE(v1=vector.sd.AD.num.women.true.cov.100.25.40, v2=vector.sd.MAR.cov.35.AD.women.cl.25.40)
MRE.error.infer.clust.cov.100.women.25.40.cov.35.sd <- MRE(error.infer.clust.cov.100.women.25.40.cov.35.sd)
# 40.50
# Mean
error.infer.clust.cov.100.men.40.50.cov.35.mean <- as.numeric(vector.mean.AD.num.men.true.cov.100.40.50) - as.numeric(vector.mean.MAR.cov.35.AD.men.cl.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.cov.35.mean <- RMSE(error.infer.clust.cov.100.men.40.50.cov.35.mean)
MAE.error.infer.clust.cov.100.men.40.50.cov.35.mean <- MAE(error.infer.clust.cov.100.men.40.50.cov.35.mean)
ARMSE.error.infer.clust.cov.100.men.40.50.cov.35 <- ARMSE(v1=vector.mean.AD.num.men.true.cov.100.40.50, v2=vector.mean.MAR.cov.35.AD.men.cl.40.50)
MRE.error.infer.clust.cov.100.men.40.50.cov.35.mean <- MRE(error.infer.clust.cov.100.men.40.50.cov.35.mean)
error.infer.clust.cov.100.women.40.50.cov.35.mean <- as.numeric(vector.mean.AD.num.women.true.cov.100.40.50) - as.numeric(vector.mean.MAR.cov.35.AD.women.cl.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.cov.35.mean <- RMSE(error.infer.clust.cov.100.women.40.50.cov.35.mean)
MAE.error.infer.clust.cov.100.women.40.50.cov.35.mean <- MAE(error.infer.clust.cov.100.women.40.50.cov.35.mean)
ARMSE.error.infer.clust.cov.100.women.40.50.cov.35.mean <- ARMSE(v1=vector.mean.AD.num.women.true.cov.100.40.50, v2=vector.mean.MAR.cov.35.AD.women.cl.40.50)
MRE.error.infer.clust.cov.100.women.40.50.cov.35.mean <- MRE(error.infer.clust.cov.100.women.40.50.cov.35.mean)
# Median
error.infer.clust.cov.100.men.40.50.cov.35.med <- as.numeric(vector.med.AD.num.men.true.cov.100.40.50) - as.numeric(vector.med.MAR.cov.35.AD.men.cl.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.cov.35.med <- RMSE(error.infer.clust.cov.100.men.40.50.cov.35.med)
MAE.error.infer.clust.cov.100.men.40.50.cov.35.med <- MAE(error.infer.clust.cov.100.men.40.50.cov.35.med)
ARMSE.error.infer.clust.cov.100.men.40.50.cov.35 <- ARMSE(v1=vector.med.AD.num.men.true.cov.100.40.50, v2=vector.med.MAR.cov.35.AD.men.cl.40.50)
MRE.error.infer.clust.cov.100.men.40.50.cov.35.med <- MRE(error.infer.clust.cov.100.men.40.50.cov.35.med)
error.infer.clust.cov.100.women.40.50.cov.35.med <- as.numeric(vector.med.AD.num.women.true.cov.100.40.50) - as.numeric(vector.med.MAR.cov.35.AD.women.cl.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.cov.35.med <- RMSE(error.infer.clust.cov.100.women.40.50.cov.35.med)
MAE.error.infer.clust.cov.100.women.40.50.cov.35.med <- MAE(error.infer.clust.cov.100.women.40.50.cov.35.med)
ARMSE.error.infer.clust.cov.100.women.40.50.cov.35.med <- ARMSE(v1=vector.med.AD.num.women.true.cov.100.40.50, v2=vector.med.MAR.cov.35.AD.women.cl.40.50)
MRE.error.infer.clust.cov.100.women.40.50.cov.35.med <- MRE(error.infer.clust.cov.100.women.40.50.cov.35.med)
# Standard deviation
error.infer.clust.cov.100.men.40.50.cov.35.sd <- as.numeric(vector.sd.AD.num.men.true.cov.100.40.50) - as.numeric(vector.sd.MAR.cov.35.AD.men.cl.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.cov.35.sd <- RMSE(error.infer.clust.cov.100.men.40.50.cov.35.sd)
MAE.error.infer.clust.cov.100.men.40.50.cov.35.sd <- MAE(error.infer.clust.cov.100.men.40.50.cov.35.sd)
ARMSE.error.infer.clust.cov.100.men.40.50.cov.35 <- ARMSE(v1=vector.sd.AD.num.men.true.cov.100.40.50, v2=vector.sd.MAR.cov.35.AD.men.cl.40.50)
MRE.error.infer.clust.cov.100.men.40.50.cov.35.sd <- MRE(error.infer.clust.cov.100.men.40.50.cov.35.sd)
error.infer.clust.cov.100.women.40.50.cov.35.sd <- as.numeric(vector.sd.AD.num.women.true.cov.100.40.50) - as.numeric(vector.sd.MAR.cov.35.AD.women.cl.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.cov.35.sd <- RMSE(error.infer.clust.cov.100.women.40.50.cov.35.sd)
MAE.error.infer.clust.cov.100.women.40.50.cov.35.sd <- MAE(error.infer.clust.cov.100.women.40.50.cov.35.sd)
ARMSE.error.infer.clust.cov.100.women.40.50.cov.35.sd <- ARMSE(v1=vector.sd.AD.num.women.true.cov.100.40.50, v2=vector.sd.MAR.cov.35.AD.women.cl.40.50)
MRE.error.infer.clust.cov.100.women.40.50.cov.35.sd <- MRE(error.infer.clust.cov.100.women.40.50.cov.35.sd)
# Cov 40
# 15.25
# Mean
error.infer.clust.cov.100.men.15.25.cov.40.mean <- as.numeric(vector.mean.AD.num.men.true.cov.100.15.25) - as.numeric(vector.mean.MAR.cov.40.AD.men.cl.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.cov.40.mean <- RMSE(error.infer.clust.cov.100.men.15.25.cov.40.mean)
MAE.error.infer.clust.cov.100.men.15.25.cov.40.mean <- MAE(error.infer.clust.cov.100.men.15.25.cov.40.mean)
ARMSE.error.infer.clust.cov.100.men.15.25.cov.40 <- ARMSE(v1=vector.mean.AD.num.men.true.cov.100.15.25, v2=vector.mean.MAR.cov.40.AD.men.cl.15.25)
MRE.error.infer.clust.cov.100.men.15.25.cov.40.mean <- MRE(error.infer.clust.cov.100.men.15.25.cov.40.mean)
error.infer.clust.cov.100.women.15.25.cov.40.mean <- as.numeric(vector.mean.AD.num.women.true.cov.100.15.25) - as.numeric(vector.mean.MAR.cov.40.AD.women.cl.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.cov.40.mean <- RMSE(error.infer.clust.cov.100.women.15.25.cov.40.mean)
MAE.error.infer.clust.cov.100.women.15.25.cov.40.mean <- MAE(error.infer.clust.cov.100.women.15.25.cov.40.mean)
ARMSE.error.infer.clust.cov.100.women.15.25.cov.40.mean <- ARMSE(v1=vector.mean.AD.num.women.true.cov.100.15.25, v2=vector.mean.MAR.cov.40.AD.women.cl.15.25)
MRE.error.infer.clust.cov.100.women.15.25.cov.40.mean <- MRE(error.infer.clust.cov.100.women.15.25.cov.40.mean)
# Median
error.infer.clust.cov.100.men.15.25.cov.40.med <- as.numeric(vector.med.AD.num.men.true.cov.100.15.25) - as.numeric(vector.med.MAR.cov.40.AD.men.cl.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.cov.40.med <- RMSE(error.infer.clust.cov.100.men.15.25.cov.40.med)
MAE.error.infer.clust.cov.100.men.15.25.cov.40.med <- MAE(error.infer.clust.cov.100.men.15.25.cov.40.med)
ARMSE.error.infer.clust.cov.100.men.15.25.cov.40 <- ARMSE(v1=vector.med.AD.num.men.true.cov.100.15.25, v2=vector.med.MAR.cov.40.AD.men.cl.15.25)
MRE.error.infer.clust.cov.100.men.15.25.cov.40.med <- MRE(error.infer.clust.cov.100.men.15.25.cov.40.med)
error.infer.clust.cov.100.women.15.25.cov.40.med <- as.numeric(vector.med.AD.num.women.true.cov.100.15.25) - as.numeric(vector.med.MAR.cov.40.AD.women.cl.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.cov.40.med <- RMSE(error.infer.clust.cov.100.women.15.25.cov.40.med)
MAE.error.infer.clust.cov.100.women.15.25.cov.40.med <- MAE(error.infer.clust.cov.100.women.15.25.cov.40.med)
ARMSE.error.infer.clust.cov.100.women.15.25.cov.40.med <- ARMSE(v1=vector.med.AD.num.women.true.cov.100.15.25, v2=vector.med.MAR.cov.40.AD.women.cl.15.25)
MRE.error.infer.clust.cov.100.women.15.25.cov.40.med <- MRE(error.infer.clust.cov.100.women.15.25.cov.40.med)
# Standard deviation
error.infer.clust.cov.100.men.15.25.cov.40.sd <- as.numeric(vector.sd.AD.num.men.true.cov.100.15.25) - as.numeric(vector.sd.MAR.cov.40.AD.men.cl.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.cov.40.sd <- RMSE(error.infer.clust.cov.100.men.15.25.cov.40.sd)
MAE.error.infer.clust.cov.100.men.15.25.cov.40.sd <- MAE(error.infer.clust.cov.100.men.15.25.cov.40.sd)
ARMSE.error.infer.clust.cov.100.men.15.25.cov.40 <- ARMSE(v1=vector.sd.AD.num.men.true.cov.100.15.25, v2=vector.sd.MAR.cov.40.AD.men.cl.15.25)
MRE.error.infer.clust.cov.100.men.15.25.cov.40.sd <- MRE(error.infer.clust.cov.100.men.15.25.cov.40.sd)
error.infer.clust.cov.100.women.15.25.cov.40.sd <- as.numeric(vector.sd.AD.num.women.true.cov.100.15.25) - as.numeric(vector.sd.MAR.cov.40.AD.women.cl.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.cov.40.sd <- RMSE(error.infer.clust.cov.100.women.15.25.cov.40.sd)
MAE.error.infer.clust.cov.100.women.15.25.cov.40.sd <- MAE(error.infer.clust.cov.100.women.15.25.cov.40.sd)
ARMSE.error.infer.clust.cov.100.women.15.25.cov.40.sd <- ARMSE(v1=vector.sd.AD.num.women.true.cov.100.15.25, v2=vector.sd.MAR.cov.40.AD.women.cl.15.25)
MRE.error.infer.clust.cov.100.women.15.25.cov.40.sd <- MRE(error.infer.clust.cov.100.women.15.25.cov.40.sd)
# 25.40
# Mean
error.infer.clust.cov.100.men.25.40.cov.40.mean <- as.numeric(vector.mean.AD.num.men.true.cov.100.25.40) - as.numeric(vector.mean.MAR.cov.40.AD.men.cl.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.cov.40.mean <- RMSE(error.infer.clust.cov.100.men.25.40.cov.40.mean)
MAE.error.infer.clust.cov.100.men.25.40.cov.40.mean <- MAE(error.infer.clust.cov.100.men.25.40.cov.40.mean)
ARMSE.error.infer.clust.cov.100.men.25.40.cov.40 <- ARMSE(v1=vector.mean.AD.num.men.true.cov.100.25.40, v2=vector.mean.MAR.cov.40.AD.men.cl.25.40)
MRE.error.infer.clust.cov.100.men.25.40.cov.40.mean <- MRE(error.infer.clust.cov.100.men.25.40.cov.40.mean)
error.infer.clust.cov.100.women.25.40.cov.40.mean <- as.numeric(vector.mean.AD.num.women.true.cov.100.25.40) - as.numeric(vector.mean.MAR.cov.40.AD.women.cl.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.cov.40.mean <- RMSE(error.infer.clust.cov.100.women.25.40.cov.40.mean)
MAE.error.infer.clust.cov.100.women.25.40.cov.40.mean <- MAE(error.infer.clust.cov.100.women.25.40.cov.40.mean)
ARMSE.error.infer.clust.cov.100.women.25.40.cov.40.mean <- ARMSE(v1=vector.mean.AD.num.women.true.cov.100.25.40, v2=vector.mean.MAR.cov.40.AD.women.cl.25.40)
MRE.error.infer.clust.cov.100.women.25.40.cov.40.mean <- MRE(error.infer.clust.cov.100.women.25.40.cov.40.mean)
# Median
error.infer.clust.cov.100.men.25.40.cov.40.med <- as.numeric(vector.med.AD.num.men.true.cov.100.25.40) - as.numeric(vector.med.MAR.cov.40.AD.men.cl.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.cov.40.med <- RMSE(error.infer.clust.cov.100.men.25.40.cov.40.med)
MAE.error.infer.clust.cov.100.men.25.40.cov.40.med <- MAE(error.infer.clust.cov.100.men.25.40.cov.40.med)
ARMSE.error.infer.clust.cov.100.men.25.40.cov.40 <- ARMSE(v1=vector.med.AD.num.men.true.cov.100.25.40, v2=vector.med.MAR.cov.40.AD.men.cl.25.40)
MRE.error.infer.clust.cov.100.men.25.40.cov.40.med <- MRE(error.infer.clust.cov.100.men.25.40.cov.40.med)
error.infer.clust.cov.100.women.25.40.cov.40.med <- as.numeric(vector.med.AD.num.women.true.cov.100.25.40) - as.numeric(vector.med.MAR.cov.40.AD.women.cl.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.cov.40.med <- RMSE(error.infer.clust.cov.100.women.25.40.cov.40.med)
MAE.error.infer.clust.cov.100.women.25.40.cov.40.med <- MAE(error.infer.clust.cov.100.women.25.40.cov.40.med)
ARMSE.error.infer.clust.cov.100.women.25.40.cov.40.med <- ARMSE(v1=vector.med.AD.num.women.true.cov.100.25.40, v2=vector.med.MAR.cov.40.AD.women.cl.25.40)
MRE.error.infer.clust.cov.100.women.25.40.cov.40.med <- MRE(error.infer.clust.cov.100.women.25.40.cov.40.med)
# Standard deviation
error.infer.clust.cov.100.men.25.40.cov.40.sd <- as.numeric(vector.sd.AD.num.men.true.cov.100.25.40) - as.numeric(vector.sd.MAR.cov.40.AD.men.cl.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.cov.40.sd <- RMSE(error.infer.clust.cov.100.men.25.40.cov.40.sd)
MAE.error.infer.clust.cov.100.men.25.40.cov.40.sd <- MAE(error.infer.clust.cov.100.men.25.40.cov.40.sd)
ARMSE.error.infer.clust.cov.100.men.25.40.cov.40 <- ARMSE(v1=vector.sd.AD.num.men.true.cov.100.25.40, v2=vector.sd.MAR.cov.40.AD.men.cl.25.40)
MRE.error.infer.clust.cov.100.men.25.40.cov.40.sd <- MRE(error.infer.clust.cov.100.men.25.40.cov.40.sd)
error.infer.clust.cov.100.women.25.40.cov.40.sd <- as.numeric(vector.sd.AD.num.women.true.cov.100.25.40) - as.numeric(vector.sd.MAR.cov.40.AD.women.cl.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.cov.40.sd <- RMSE(error.infer.clust.cov.100.women.25.40.cov.40.sd)
MAE.error.infer.clust.cov.100.women.25.40.cov.40.sd <- MAE(error.infer.clust.cov.100.women.25.40.cov.40.sd)
ARMSE.error.infer.clust.cov.100.women.25.40.cov.40.sd <- ARMSE(v1=vector.sd.AD.num.women.true.cov.100.25.40, v2=vector.sd.MAR.cov.40.AD.women.cl.25.40)
MRE.error.infer.clust.cov.100.women.25.40.cov.40.sd <- MRE(error.infer.clust.cov.100.women.25.40.cov.40.sd)
# 40.50
# Mean
error.infer.clust.cov.100.men.40.50.cov.40.mean <- as.numeric(vector.mean.AD.num.men.true.cov.100.40.50) - as.numeric(vector.mean.MAR.cov.40.AD.men.cl.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.cov.40.mean <- RMSE(error.infer.clust.cov.100.men.40.50.cov.40.mean)
MAE.error.infer.clust.cov.100.men.40.50.cov.40.mean <- MAE(error.infer.clust.cov.100.men.40.50.cov.40.mean)
ARMSE.error.infer.clust.cov.100.men.40.50.cov.40 <- ARMSE(v1=vector.mean.AD.num.men.true.cov.100.40.50, v2=vector.mean.MAR.cov.40.AD.men.cl.40.50)
MRE.error.infer.clust.cov.100.men.40.50.cov.40.mean <- MRE(error.infer.clust.cov.100.men.40.50.cov.40.mean)
error.infer.clust.cov.100.women.40.50.cov.40.mean <- as.numeric(vector.mean.AD.num.women.true.cov.100.40.50) - as.numeric(vector.mean.MAR.cov.40.AD.women.cl.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.cov.40.mean <- RMSE(error.infer.clust.cov.100.women.40.50.cov.40.mean)
MAE.error.infer.clust.cov.100.women.40.50.cov.40.mean <- MAE(error.infer.clust.cov.100.women.40.50.cov.40.mean)
ARMSE.error.infer.clust.cov.100.women.40.50.cov.40.mean <- ARMSE(v1=vector.mean.AD.num.women.true.cov.100.40.50, v2=vector.mean.MAR.cov.40.AD.women.cl.40.50)
MRE.error.infer.clust.cov.100.women.40.50.cov.40.mean <- MRE(error.infer.clust.cov.100.women.40.50.cov.40.mean)
# Median
error.infer.clust.cov.100.men.40.50.cov.40.med <- as.numeric(vector.med.AD.num.men.true.cov.100.40.50) - as.numeric(vector.med.MAR.cov.40.AD.men.cl.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.cov.40.med <- RMSE(error.infer.clust.cov.100.men.40.50.cov.40.med)
MAE.error.infer.clust.cov.100.men.40.50.cov.40.med <- MAE(error.infer.clust.cov.100.men.40.50.cov.40.med)
ARMSE.error.infer.clust.cov.100.men.40.50.cov.40 <- ARMSE(v1=vector.med.AD.num.men.true.cov.100.40.50, v2=vector.med.MAR.cov.40.AD.men.cl.40.50)
MRE.error.infer.clust.cov.100.men.40.50.cov.40.med <- MRE(error.infer.clust.cov.100.men.40.50.cov.40.med)
error.infer.clust.cov.100.women.40.50.cov.40.med <- as.numeric(vector.med.AD.num.women.true.cov.100.40.50) - as.numeric(vector.med.MAR.cov.40.AD.women.cl.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.cov.40.med <- RMSE(error.infer.clust.cov.100.women.40.50.cov.40.med)
MAE.error.infer.clust.cov.100.women.40.50.cov.40.med <- MAE(error.infer.clust.cov.100.women.40.50.cov.40.med)
ARMSE.error.infer.clust.cov.100.women.40.50.cov.40.med <- ARMSE(v1=vector.med.AD.num.women.true.cov.100.40.50, v2=vector.med.MAR.cov.40.AD.women.cl.40.50)
MRE.error.infer.clust.cov.100.women.40.50.cov.40.med <- MRE(error.infer.clust.cov.100.women.40.50.cov.40.med)
# Standard deviation
error.infer.clust.cov.100.men.40.50.cov.40.sd <- as.numeric(vector.sd.AD.num.men.true.cov.100.40.50) - as.numeric(vector.sd.MAR.cov.40.AD.men.cl.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.cov.40.sd <- RMSE(error.infer.clust.cov.100.men.40.50.cov.40.sd)
MAE.error.infer.clust.cov.100.men.40.50.cov.40.sd <- MAE(error.infer.clust.cov.100.men.40.50.cov.40.sd)
ARMSE.error.infer.clust.cov.100.men.40.50.cov.40 <- ARMSE(v1=vector.sd.AD.num.men.true.cov.100.40.50, v2=vector.sd.MAR.cov.40.AD.men.cl.40.50)
MRE.error.infer.clust.cov.100.men.40.50.cov.40.sd <- MRE(error.infer.clust.cov.100.men.40.50.cov.40.sd)
error.infer.clust.cov.100.women.40.50.cov.40.sd <- as.numeric(vector.sd.AD.num.women.true.cov.100.40.50) - as.numeric(vector.sd.MAR.cov.40.AD.women.cl.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.cov.40.sd <- RMSE(error.infer.clust.cov.100.women.40.50.cov.40.sd)
MAE.error.infer.clust.cov.100.women.40.50.cov.40.sd <- MAE(error.infer.clust.cov.100.women.40.50.cov.40.sd)
ARMSE.error.infer.clust.cov.100.women.40.50.cov.40.sd <- ARMSE(v1=vector.sd.AD.num.women.true.cov.100.40.50, v2=vector.sd.MAR.cov.40.AD.women.cl.40.50)
MRE.error.infer.clust.cov.100.women.40.50.cov.40.sd <- MRE(error.infer.clust.cov.100.women.40.50.cov.40.sd)
# Cov 45
# 15.25
# Mean
error.infer.clust.cov.100.men.15.25.cov.45.mean <- as.numeric(vector.mean.AD.num.men.true.cov.100.15.25) - as.numeric(vector.mean.MAR.cov.45.AD.men.cl.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.cov.45.mean <- RMSE(error.infer.clust.cov.100.men.15.25.cov.45.mean)
MAE.error.infer.clust.cov.100.men.15.25.cov.45.mean <- MAE(error.infer.clust.cov.100.men.15.25.cov.45.mean)
ARMSE.error.infer.clust.cov.100.men.15.25.cov.45 <- ARMSE(v1=vector.mean.AD.num.men.true.cov.100.15.25, v2=vector.mean.MAR.cov.45.AD.men.cl.15.25)
MRE.error.infer.clust.cov.100.men.15.25.cov.45.mean <- MRE(error.infer.clust.cov.100.men.15.25.cov.45.mean)
error.infer.clust.cov.100.women.15.25.cov.45.mean <- as.numeric(vector.mean.AD.num.women.true.cov.100.15.25) - as.numeric(vector.mean.MAR.cov.45.AD.women.cl.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.cov.45.mean <- RMSE(error.infer.clust.cov.100.women.15.25.cov.45.mean)
MAE.error.infer.clust.cov.100.women.15.25.cov.45.mean <- MAE(error.infer.clust.cov.100.women.15.25.cov.45.mean)
ARMSE.error.infer.clust.cov.100.women.15.25.cov.45.mean <- ARMSE(v1=vector.mean.AD.num.women.true.cov.100.15.25, v2=vector.mean.MAR.cov.45.AD.women.cl.15.25)
MRE.error.infer.clust.cov.100.women.15.25.cov.45.mean <- MRE(error.infer.clust.cov.100.women.15.25.cov.45.mean)
# Median
error.infer.clust.cov.100.men.15.25.cov.45.med <- as.numeric(vector.med.AD.num.men.true.cov.100.15.25) - as.numeric(vector.med.MAR.cov.45.AD.men.cl.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.cov.45.med <- RMSE(error.infer.clust.cov.100.men.15.25.cov.45.med)
MAE.error.infer.clust.cov.100.men.15.25.cov.45.med <- MAE(error.infer.clust.cov.100.men.15.25.cov.45.med)
ARMSE.error.infer.clust.cov.100.men.15.25.cov.45 <- ARMSE(v1=vector.med.AD.num.men.true.cov.100.15.25, v2=vector.med.MAR.cov.45.AD.men.cl.15.25)
MRE.error.infer.clust.cov.100.men.15.25.cov.45.med <- MRE(error.infer.clust.cov.100.men.15.25.cov.45.med)
error.infer.clust.cov.100.women.15.25.cov.45.med <- as.numeric(vector.med.AD.num.women.true.cov.100.15.25) - as.numeric(vector.med.MAR.cov.45.AD.women.cl.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.cov.45.med <- RMSE(error.infer.clust.cov.100.women.15.25.cov.45.med)
MAE.error.infer.clust.cov.100.women.15.25.cov.45.med <- MAE(error.infer.clust.cov.100.women.15.25.cov.45.med)
ARMSE.error.infer.clust.cov.100.women.15.25.cov.45.med <- ARMSE(v1=vector.med.AD.num.women.true.cov.100.15.25, v2=vector.med.MAR.cov.45.AD.women.cl.15.25)
MRE.error.infer.clust.cov.100.women.15.25.cov.45.med <- MRE(error.infer.clust.cov.100.women.15.25.cov.45.med)
# Standard deviation
error.infer.clust.cov.100.men.15.25.cov.45.sd <- as.numeric(vector.sd.AD.num.men.true.cov.100.15.25) - as.numeric(vector.sd.MAR.cov.45.AD.men.cl.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.cov.45.sd <- RMSE(error.infer.clust.cov.100.men.15.25.cov.45.sd)
MAE.error.infer.clust.cov.100.men.15.25.cov.45.sd <- MAE(error.infer.clust.cov.100.men.15.25.cov.45.sd)
ARMSE.error.infer.clust.cov.100.men.15.25.cov.45 <- ARMSE(v1=vector.sd.AD.num.men.true.cov.100.15.25, v2=vector.sd.MAR.cov.45.AD.men.cl.15.25)
MRE.error.infer.clust.cov.100.men.15.25.cov.45.sd <- MRE(error.infer.clust.cov.100.men.15.25.cov.45.sd)
error.infer.clust.cov.100.women.15.25.cov.45.sd <- as.numeric(vector.sd.AD.num.women.true.cov.100.15.25) - as.numeric(vector.sd.MAR.cov.45.AD.women.cl.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.cov.45.sd <- RMSE(error.infer.clust.cov.100.women.15.25.cov.45.sd)
MAE.error.infer.clust.cov.100.women.15.25.cov.45.sd <- MAE(error.infer.clust.cov.100.women.15.25.cov.45.sd)
ARMSE.error.infer.clust.cov.100.women.15.25.cov.45.sd <- ARMSE(v1=vector.sd.AD.num.women.true.cov.100.15.25, v2=vector.sd.MAR.cov.45.AD.women.cl.15.25)
MRE.error.infer.clust.cov.100.women.15.25.cov.45.sd <- MRE(error.infer.clust.cov.100.women.15.25.cov.45.sd)
# 25.40
# Mean
error.infer.clust.cov.100.men.25.40.cov.45.mean <- as.numeric(vector.mean.AD.num.men.true.cov.100.25.40) - as.numeric(vector.mean.MAR.cov.45.AD.men.cl.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.cov.45.mean <- RMSE(error.infer.clust.cov.100.men.25.40.cov.45.mean)
MAE.error.infer.clust.cov.100.men.25.40.cov.45.mean <- MAE(error.infer.clust.cov.100.men.25.40.cov.45.mean)
ARMSE.error.infer.clust.cov.100.men.25.40.cov.45 <- ARMSE(v1=vector.mean.AD.num.men.true.cov.100.25.40, v2=vector.mean.MAR.cov.45.AD.men.cl.25.40)
MRE.error.infer.clust.cov.100.men.25.40.cov.45.mean <- MRE(error.infer.clust.cov.100.men.25.40.cov.45.mean)
error.infer.clust.cov.100.women.25.40.cov.45.mean <- as.numeric(vector.mean.AD.num.women.true.cov.100.25.40) - as.numeric(vector.mean.MAR.cov.45.AD.women.cl.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.cov.45.mean <- RMSE(error.infer.clust.cov.100.women.25.40.cov.45.mean)
MAE.error.infer.clust.cov.100.women.25.40.cov.45.mean <- MAE(error.infer.clust.cov.100.women.25.40.cov.45.mean)
ARMSE.error.infer.clust.cov.100.women.25.40.cov.45.mean <- ARMSE(v1=vector.mean.AD.num.women.true.cov.100.25.40, v2=vector.mean.MAR.cov.45.AD.women.cl.25.40)
MRE.error.infer.clust.cov.100.women.25.40.cov.45.mean <- MRE(error.infer.clust.cov.100.women.25.40.cov.45.mean)
# Median
error.infer.clust.cov.100.men.25.40.cov.45.med <- as.numeric(vector.med.AD.num.men.true.cov.100.25.40) - as.numeric(vector.med.MAR.cov.45.AD.men.cl.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.cov.45.med <- RMSE(error.infer.clust.cov.100.men.25.40.cov.45.med)
MAE.error.infer.clust.cov.100.men.25.40.cov.45.med <- MAE(error.infer.clust.cov.100.men.25.40.cov.45.med)
ARMSE.error.infer.clust.cov.100.men.25.40.cov.45 <- ARMSE(v1=vector.med.AD.num.men.true.cov.100.25.40, v2=vector.med.MAR.cov.45.AD.men.cl.25.40)
MRE.error.infer.clust.cov.100.men.25.40.cov.45.med <- MRE(error.infer.clust.cov.100.men.25.40.cov.45.med)
error.infer.clust.cov.100.women.25.40.cov.45.med <- as.numeric(vector.med.AD.num.women.true.cov.100.25.40) - as.numeric(vector.med.MAR.cov.45.AD.women.cl.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.cov.45.med <- RMSE(error.infer.clust.cov.100.women.25.40.cov.45.med)
MAE.error.infer.clust.cov.100.women.25.40.cov.45.med <- MAE(error.infer.clust.cov.100.women.25.40.cov.45.med)
ARMSE.error.infer.clust.cov.100.women.25.40.cov.45.med <- ARMSE(v1=vector.med.AD.num.women.true.cov.100.25.40, v2=vector.med.MAR.cov.45.AD.women.cl.25.40)
MRE.error.infer.clust.cov.100.women.25.40.cov.45.med <- MRE(error.infer.clust.cov.100.women.25.40.cov.45.med)
# Standard deviation
error.infer.clust.cov.100.men.25.40.cov.45.sd <- as.numeric(vector.sd.AD.num.men.true.cov.100.25.40) - as.numeric(vector.sd.MAR.cov.45.AD.men.cl.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.cov.45.sd <- RMSE(error.infer.clust.cov.100.men.25.40.cov.45.sd)
MAE.error.infer.clust.cov.100.men.25.40.cov.45.sd <- MAE(error.infer.clust.cov.100.men.25.40.cov.45.sd)
ARMSE.error.infer.clust.cov.100.men.25.40.cov.45 <- ARMSE(v1=vector.sd.AD.num.men.true.cov.100.25.40, v2=vector.sd.MAR.cov.45.AD.men.cl.25.40)
MRE.error.infer.clust.cov.100.men.25.40.cov.45.sd <- MRE(error.infer.clust.cov.100.men.25.40.cov.45.sd)
error.infer.clust.cov.100.women.25.40.cov.45.sd <- as.numeric(vector.sd.AD.num.women.true.cov.100.25.40) - as.numeric(vector.sd.MAR.cov.45.AD.women.cl.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.cov.45.sd <- RMSE(error.infer.clust.cov.100.women.25.40.cov.45.sd)
MAE.error.infer.clust.cov.100.women.25.40.cov.45.sd <- MAE(error.infer.clust.cov.100.women.25.40.cov.45.sd)
ARMSE.error.infer.clust.cov.100.women.25.40.cov.45.sd <- ARMSE(v1=vector.sd.AD.num.women.true.cov.100.25.40, v2=vector.sd.MAR.cov.45.AD.women.cl.25.40)
MRE.error.infer.clust.cov.100.women.25.40.cov.45.sd <- MRE(error.infer.clust.cov.100.women.25.40.cov.45.sd)
# 40.50
# Mean
error.infer.clust.cov.100.men.40.50.cov.45.mean <- as.numeric(vector.mean.AD.num.men.true.cov.100.40.50) - as.numeric(vector.mean.MAR.cov.45.AD.men.cl.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.cov.45.mean <- RMSE(error.infer.clust.cov.100.men.40.50.cov.45.mean)
MAE.error.infer.clust.cov.100.men.40.50.cov.45.mean <- MAE(error.infer.clust.cov.100.men.40.50.cov.45.mean)
ARMSE.error.infer.clust.cov.100.men.40.50.cov.45 <- ARMSE(v1=vector.mean.AD.num.men.true.cov.100.40.50, v2=vector.mean.MAR.cov.45.AD.men.cl.40.50)
MRE.error.infer.clust.cov.100.men.40.50.cov.45.mean <- MRE(error.infer.clust.cov.100.men.40.50.cov.45.mean)
error.infer.clust.cov.100.women.40.50.cov.45.mean <- as.numeric(vector.mean.AD.num.women.true.cov.100.40.50) - as.numeric(vector.mean.MAR.cov.45.AD.women.cl.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.cov.45.mean <- RMSE(error.infer.clust.cov.100.women.40.50.cov.45.mean)
MAE.error.infer.clust.cov.100.women.40.50.cov.45.mean <- MAE(error.infer.clust.cov.100.women.40.50.cov.45.mean)
ARMSE.error.infer.clust.cov.100.women.40.50.cov.45.mean <- ARMSE(v1=vector.mean.AD.num.women.true.cov.100.40.50, v2=vector.mean.MAR.cov.45.AD.women.cl.40.50)
MRE.error.infer.clust.cov.100.women.40.50.cov.45.mean <- MRE(error.infer.clust.cov.100.women.40.50.cov.45.mean)
# Median
error.infer.clust.cov.100.men.40.50.cov.45.med <- as.numeric(vector.med.AD.num.men.true.cov.100.40.50) - as.numeric(vector.med.MAR.cov.45.AD.men.cl.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.cov.45.med <- RMSE(error.infer.clust.cov.100.men.40.50.cov.45.med)
MAE.error.infer.clust.cov.100.men.40.50.cov.45.med <- MAE(error.infer.clust.cov.100.men.40.50.cov.45.med)
ARMSE.error.infer.clust.cov.100.men.40.50.cov.45 <- ARMSE(v1=vector.med.AD.num.men.true.cov.100.40.50, v2=vector.med.MAR.cov.45.AD.men.cl.40.50)
MRE.error.infer.clust.cov.100.men.40.50.cov.45.med <- MRE(error.infer.clust.cov.100.men.40.50.cov.45.med)
error.infer.clust.cov.100.women.40.50.cov.45.med <- as.numeric(vector.med.AD.num.women.true.cov.100.40.50) - as.numeric(vector.med.MAR.cov.45.AD.women.cl.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.cov.45.med <- RMSE(error.infer.clust.cov.100.women.40.50.cov.45.med)
MAE.error.infer.clust.cov.100.women.40.50.cov.45.med <- MAE(error.infer.clust.cov.100.women.40.50.cov.45.med)
ARMSE.error.infer.clust.cov.100.women.40.50.cov.45.med <- ARMSE(v1=vector.med.AD.num.women.true.cov.100.40.50, v2=vector.med.MAR.cov.45.AD.women.cl.40.50)
MRE.error.infer.clust.cov.100.women.40.50.cov.45.med <- MRE(error.infer.clust.cov.100.women.40.50.cov.45.med)
# Standard deviation
error.infer.clust.cov.100.men.40.50.cov.45.sd <- as.numeric(vector.sd.AD.num.men.true.cov.100.40.50) - as.numeric(vector.sd.MAR.cov.45.AD.men.cl.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.cov.45.sd <- RMSE(error.infer.clust.cov.100.men.40.50.cov.45.sd)
MAE.error.infer.clust.cov.100.men.40.50.cov.45.sd <- MAE(error.infer.clust.cov.100.men.40.50.cov.45.sd)
ARMSE.error.infer.clust.cov.100.men.40.50.cov.45 <- ARMSE(v1=vector.sd.AD.num.men.true.cov.100.40.50, v2=vector.sd.MAR.cov.45.AD.men.cl.40.50)
MRE.error.infer.clust.cov.100.men.40.50.cov.45.sd <- MRE(error.infer.clust.cov.100.men.40.50.cov.45.sd)
error.infer.clust.cov.100.women.40.50.cov.45.sd <- as.numeric(vector.sd.AD.num.women.true.cov.100.40.50) - as.numeric(vector.sd.MAR.cov.45.AD.women.cl.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.cov.45.sd <- RMSE(error.infer.clust.cov.100.women.40.50.cov.45.sd)
MAE.error.infer.clust.cov.100.women.40.50.cov.45.sd <- MAE(error.infer.clust.cov.100.women.40.50.cov.45.sd)
ARMSE.error.infer.clust.cov.100.women.40.50.cov.45.sd <- ARMSE(v1=vector.sd.AD.num.women.true.cov.100.40.50, v2=vector.sd.MAR.cov.45.AD.women.cl.40.50)
MRE.error.infer.clust.cov.100.women.40.50.cov.45.sd <- MRE(error.infer.clust.cov.100.women.40.50.cov.45.sd)
# Cov 50
# 15.25
# Mean
error.infer.clust.cov.100.men.15.25.cov.50.mean <- as.numeric(vector.mean.AD.num.men.true.cov.100.15.25) - as.numeric(vector.mean.MAR.cov.50.AD.men.cl.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.cov.50.mean <- RMSE(error.infer.clust.cov.100.men.15.25.cov.50.mean)
MAE.error.infer.clust.cov.100.men.15.25.cov.50.mean <- MAE(error.infer.clust.cov.100.men.15.25.cov.50.mean)
ARMSE.error.infer.clust.cov.100.men.15.25.cov.50 <- ARMSE(v1=vector.mean.AD.num.men.true.cov.100.15.25, v2=vector.mean.MAR.cov.50.AD.men.cl.15.25)
MRE.error.infer.clust.cov.100.men.15.25.cov.50.mean <- MRE(error.infer.clust.cov.100.men.15.25.cov.50.mean)
error.infer.clust.cov.100.women.15.25.cov.50.mean <- as.numeric(vector.mean.AD.num.women.true.cov.100.15.25) - as.numeric(vector.mean.MAR.cov.50.AD.women.cl.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.cov.50.mean <- RMSE(error.infer.clust.cov.100.women.15.25.cov.50.mean)
MAE.error.infer.clust.cov.100.women.15.25.cov.50.mean <- MAE(error.infer.clust.cov.100.women.15.25.cov.50.mean)
ARMSE.error.infer.clust.cov.100.women.15.25.cov.50.mean <- ARMSE(v1=vector.mean.AD.num.women.true.cov.100.15.25, v2=vector.mean.MAR.cov.50.AD.women.cl.15.25)
MRE.error.infer.clust.cov.100.women.15.25.cov.50.mean <- MRE(error.infer.clust.cov.100.women.15.25.cov.50.mean)
# Median
error.infer.clust.cov.100.men.15.25.cov.50.med <- as.numeric(vector.med.AD.num.men.true.cov.100.15.25) - as.numeric(vector.med.MAR.cov.50.AD.men.cl.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.cov.50.med <- RMSE(error.infer.clust.cov.100.men.15.25.cov.50.med)
MAE.error.infer.clust.cov.100.men.15.25.cov.50.med <- MAE(error.infer.clust.cov.100.men.15.25.cov.50.med)
ARMSE.error.infer.clust.cov.100.men.15.25.cov.50 <- ARMSE(v1=vector.med.AD.num.men.true.cov.100.15.25, v2=vector.med.MAR.cov.50.AD.men.cl.15.25)
MRE.error.infer.clust.cov.100.men.15.25.cov.50.med <- MRE(error.infer.clust.cov.100.men.15.25.cov.50.med)
error.infer.clust.cov.100.women.15.25.cov.50.med <- as.numeric(vector.med.AD.num.women.true.cov.100.15.25) - as.numeric(vector.med.MAR.cov.50.AD.women.cl.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.cov.50.med <- RMSE(error.infer.clust.cov.100.women.15.25.cov.50.med)
MAE.error.infer.clust.cov.100.women.15.25.cov.50.med <- MAE(error.infer.clust.cov.100.women.15.25.cov.50.med)
ARMSE.error.infer.clust.cov.100.women.15.25.cov.50.med <- ARMSE(v1=vector.med.AD.num.women.true.cov.100.15.25, v2=vector.med.MAR.cov.50.AD.women.cl.15.25)
MRE.error.infer.clust.cov.100.women.15.25.cov.50.med <- MRE(error.infer.clust.cov.100.women.15.25.cov.50.med)
# Standard deviation
error.infer.clust.cov.100.men.15.25.cov.50.sd <- as.numeric(vector.sd.AD.num.men.true.cov.100.15.25) - as.numeric(vector.sd.MAR.cov.50.AD.men.cl.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.cov.50.sd <- RMSE(error.infer.clust.cov.100.men.15.25.cov.50.sd)
MAE.error.infer.clust.cov.100.men.15.25.cov.50.sd <- MAE(error.infer.clust.cov.100.men.15.25.cov.50.sd)
ARMSE.error.infer.clust.cov.100.men.15.25.cov.50 <- ARMSE(v1=vector.sd.AD.num.men.true.cov.100.15.25, v2=vector.sd.MAR.cov.50.AD.men.cl.15.25)
MRE.error.infer.clust.cov.100.men.15.25.cov.50.sd <- MRE(error.infer.clust.cov.100.men.15.25.cov.50.sd)
error.infer.clust.cov.100.women.15.25.cov.50.sd <- as.numeric(vector.sd.AD.num.women.true.cov.100.15.25) - as.numeric(vector.sd.MAR.cov.50.AD.women.cl.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.cov.50.sd <- RMSE(error.infer.clust.cov.100.women.15.25.cov.50.sd)
MAE.error.infer.clust.cov.100.women.15.25.cov.50.sd <- MAE(error.infer.clust.cov.100.women.15.25.cov.50.sd)
ARMSE.error.infer.clust.cov.100.women.15.25.cov.50.sd <- ARMSE(v1=vector.sd.AD.num.women.true.cov.100.15.25, v2=vector.sd.MAR.cov.50.AD.women.cl.15.25)
MRE.error.infer.clust.cov.100.women.15.25.cov.50.sd <- MRE(error.infer.clust.cov.100.women.15.25.cov.50.sd)
# 25.40
# Mean
error.infer.clust.cov.100.men.25.40.cov.50.mean <- as.numeric(vector.mean.AD.num.men.true.cov.100.25.40) - as.numeric(vector.mean.MAR.cov.50.AD.men.cl.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.cov.50.mean <- RMSE(error.infer.clust.cov.100.men.25.40.cov.50.mean)
MAE.error.infer.clust.cov.100.men.25.40.cov.50.mean <- MAE(error.infer.clust.cov.100.men.25.40.cov.50.mean)
ARMSE.error.infer.clust.cov.100.men.25.40.cov.50 <- ARMSE(v1=vector.mean.AD.num.men.true.cov.100.25.40, v2=vector.mean.MAR.cov.50.AD.men.cl.25.40)
MRE.error.infer.clust.cov.100.men.25.40.cov.50.mean <- MRE(error.infer.clust.cov.100.men.25.40.cov.50.mean)
error.infer.clust.cov.100.women.25.40.cov.50.mean <- as.numeric(vector.mean.AD.num.women.true.cov.100.25.40) - as.numeric(vector.mean.MAR.cov.50.AD.women.cl.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.cov.50.mean <- RMSE(error.infer.clust.cov.100.women.25.40.cov.50.mean)
MAE.error.infer.clust.cov.100.women.25.40.cov.50.mean <- MAE(error.infer.clust.cov.100.women.25.40.cov.50.mean)
ARMSE.error.infer.clust.cov.100.women.25.40.cov.50.mean <- ARMSE(v1=vector.mean.AD.num.women.true.cov.100.25.40, v2=vector.mean.MAR.cov.50.AD.women.cl.25.40)
MRE.error.infer.clust.cov.100.women.25.40.cov.50.mean <- MRE(error.infer.clust.cov.100.women.25.40.cov.50.mean)
# Median
error.infer.clust.cov.100.men.25.40.cov.50.med <- as.numeric(vector.med.AD.num.men.true.cov.100.25.40) - as.numeric(vector.med.MAR.cov.50.AD.men.cl.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.cov.50.med <- RMSE(error.infer.clust.cov.100.men.25.40.cov.50.med)
MAE.error.infer.clust.cov.100.men.25.40.cov.50.med <- MAE(error.infer.clust.cov.100.men.25.40.cov.50.med)
ARMSE.error.infer.clust.cov.100.men.25.40.cov.50 <- ARMSE(v1=vector.med.AD.num.men.true.cov.100.25.40, v2=vector.med.MAR.cov.50.AD.men.cl.25.40)
MRE.error.infer.clust.cov.100.men.25.40.cov.50.med <- MRE(error.infer.clust.cov.100.men.25.40.cov.50.med)
error.infer.clust.cov.100.women.25.40.cov.50.med <- as.numeric(vector.med.AD.num.women.true.cov.100.25.40) - as.numeric(vector.med.MAR.cov.50.AD.women.cl.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.cov.50.med <- RMSE(error.infer.clust.cov.100.women.25.40.cov.50.med)
MAE.error.infer.clust.cov.100.women.25.40.cov.50.med <- MAE(error.infer.clust.cov.100.women.25.40.cov.50.med)
ARMSE.error.infer.clust.cov.100.women.25.40.cov.50.med <- ARMSE(v1=vector.med.AD.num.women.true.cov.100.25.40, v2=vector.med.MAR.cov.50.AD.women.cl.25.40)
MRE.error.infer.clust.cov.100.women.25.40.cov.50.med <- MRE(error.infer.clust.cov.100.women.25.40.cov.50.med)
# Standard deviation
error.infer.clust.cov.100.men.25.40.cov.50.sd <- as.numeric(vector.sd.AD.num.men.true.cov.100.25.40) - as.numeric(vector.sd.MAR.cov.50.AD.men.cl.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.cov.50.sd <- RMSE(error.infer.clust.cov.100.men.25.40.cov.50.sd)
MAE.error.infer.clust.cov.100.men.25.40.cov.50.sd <- MAE(error.infer.clust.cov.100.men.25.40.cov.50.sd)
ARMSE.error.infer.clust.cov.100.men.25.40.cov.50 <- ARMSE(v1=vector.sd.AD.num.men.true.cov.100.25.40, v2=vector.sd.MAR.cov.50.AD.men.cl.25.40)
MRE.error.infer.clust.cov.100.men.25.40.cov.50.sd <- MRE(error.infer.clust.cov.100.men.25.40.cov.50.sd)
error.infer.clust.cov.100.women.25.40.cov.50.sd <- as.numeric(vector.sd.AD.num.women.true.cov.100.25.40) - as.numeric(vector.sd.MAR.cov.50.AD.women.cl.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.cov.50.sd <- RMSE(error.infer.clust.cov.100.women.25.40.cov.50.sd)
MAE.error.infer.clust.cov.100.women.25.40.cov.50.sd <- MAE(error.infer.clust.cov.100.women.25.40.cov.50.sd)
ARMSE.error.infer.clust.cov.100.women.25.40.cov.50.sd <- ARMSE(v1=vector.sd.AD.num.women.true.cov.100.25.40, v2=vector.sd.MAR.cov.50.AD.women.cl.25.40)
MRE.error.infer.clust.cov.100.women.25.40.cov.50.sd <- MRE(error.infer.clust.cov.100.women.25.40.cov.50.sd)
# 40.50
# Mean
error.infer.clust.cov.100.men.40.50.cov.50.mean <- as.numeric(vector.mean.AD.num.men.true.cov.100.40.50) - as.numeric(vector.mean.MAR.cov.50.AD.men.cl.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.cov.50.mean <- RMSE(error.infer.clust.cov.100.men.40.50.cov.50.mean)
MAE.error.infer.clust.cov.100.men.40.50.cov.50.mean <- MAE(error.infer.clust.cov.100.men.40.50.cov.50.mean)
ARMSE.error.infer.clust.cov.100.men.40.50.cov.50 <- ARMSE(v1=vector.mean.AD.num.men.true.cov.100.40.50, v2=vector.mean.MAR.cov.50.AD.men.cl.40.50)
MRE.error.infer.clust.cov.100.men.40.50.cov.50.mean <- MRE(error.infer.clust.cov.100.men.40.50.cov.50.mean)
error.infer.clust.cov.100.women.40.50.cov.50.mean <- as.numeric(vector.mean.AD.num.women.true.cov.100.40.50) - as.numeric(vector.mean.MAR.cov.50.AD.women.cl.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.cov.50.mean <- RMSE(error.infer.clust.cov.100.women.40.50.cov.50.mean)
MAE.error.infer.clust.cov.100.women.40.50.cov.50.mean <- MAE(error.infer.clust.cov.100.women.40.50.cov.50.mean)
ARMSE.error.infer.clust.cov.100.women.40.50.cov.50.mean <- ARMSE(v1=vector.mean.AD.num.women.true.cov.100.40.50, v2=vector.mean.MAR.cov.50.AD.women.cl.40.50)
MRE.error.infer.clust.cov.100.women.40.50.cov.50.mean <- MRE(error.infer.clust.cov.100.women.40.50.cov.50.mean)
# Median
error.infer.clust.cov.100.men.40.50.cov.50.med <- as.numeric(vector.med.AD.num.men.true.cov.100.40.50) - as.numeric(vector.med.MAR.cov.50.AD.men.cl.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.cov.50.med <- RMSE(error.infer.clust.cov.100.men.40.50.cov.50.med)
MAE.error.infer.clust.cov.100.men.40.50.cov.50.med <- MAE(error.infer.clust.cov.100.men.40.50.cov.50.med)
ARMSE.error.infer.clust.cov.100.men.40.50.cov.50 <- ARMSE(v1=vector.med.AD.num.men.true.cov.100.40.50, v2=vector.med.MAR.cov.50.AD.men.cl.40.50)
MRE.error.infer.clust.cov.100.men.40.50.cov.50.med <- MRE(error.infer.clust.cov.100.men.40.50.cov.50.med)
error.infer.clust.cov.100.women.40.50.cov.50.med <- as.numeric(vector.med.AD.num.women.true.cov.100.40.50) - as.numeric(vector.med.MAR.cov.50.AD.women.cl.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.cov.50.med <- RMSE(error.infer.clust.cov.100.women.40.50.cov.50.med)
MAE.error.infer.clust.cov.100.women.40.50.cov.50.med <- MAE(error.infer.clust.cov.100.women.40.50.cov.50.med)
ARMSE.error.infer.clust.cov.100.women.40.50.cov.50.med <- ARMSE(v1=vector.med.AD.num.women.true.cov.100.40.50, v2=vector.med.MAR.cov.50.AD.women.cl.40.50)
MRE.error.infer.clust.cov.100.women.40.50.cov.50.med <- MRE(error.infer.clust.cov.100.women.40.50.cov.50.med)
# Standard deviation
error.infer.clust.cov.100.men.40.50.cov.50.sd <- as.numeric(vector.sd.AD.num.men.true.cov.100.40.50) - as.numeric(vector.sd.MAR.cov.50.AD.men.cl.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.cov.50.sd <- RMSE(error.infer.clust.cov.100.men.40.50.cov.50.sd)
MAE.error.infer.clust.cov.100.men.40.50.cov.50.sd <- MAE(error.infer.clust.cov.100.men.40.50.cov.50.sd)
ARMSE.error.infer.clust.cov.100.men.40.50.cov.50 <- ARMSE(v1=vector.sd.AD.num.men.true.cov.100.40.50, v2=vector.sd.MAR.cov.50.AD.men.cl.40.50)
MRE.error.infer.clust.cov.100.men.40.50.cov.50.sd <- MRE(error.infer.clust.cov.100.men.40.50.cov.50.sd)
error.infer.clust.cov.100.women.40.50.cov.50.sd <- as.numeric(vector.sd.AD.num.women.true.cov.100.40.50) - as.numeric(vector.sd.MAR.cov.50.AD.women.cl.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.cov.50.sd <- RMSE(error.infer.clust.cov.100.women.40.50.cov.50.sd)
MAE.error.infer.clust.cov.100.women.40.50.cov.50.sd <- MAE(error.infer.clust.cov.100.women.40.50.cov.50.sd)
ARMSE.error.infer.clust.cov.100.women.40.50.cov.50.sd <- ARMSE(v1=vector.sd.AD.num.women.true.cov.100.40.50, v2=vector.sd.MAR.cov.50.AD.women.cl.40.50)
MRE.error.infer.clust.cov.100.women.40.50.cov.50.sd <- MRE(error.infer.clust.cov.100.women.40.50.cov.50.sd)
# Cov 55
# 15.25
# Mean
error.infer.clust.cov.100.men.15.25.cov.55.mean <- as.numeric(vector.mean.AD.num.men.true.cov.100.15.25) - as.numeric(vector.mean.MAR.cov.55.AD.men.cl.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.cov.55.mean <- RMSE(error.infer.clust.cov.100.men.15.25.cov.55.mean)
MAE.error.infer.clust.cov.100.men.15.25.cov.55.mean <- MAE(error.infer.clust.cov.100.men.15.25.cov.55.mean)
ARMSE.error.infer.clust.cov.100.men.15.25.cov.55 <- ARMSE(v1=vector.mean.AD.num.men.true.cov.100.15.25, v2=vector.mean.MAR.cov.55.AD.men.cl.15.25)
MRE.error.infer.clust.cov.100.men.15.25.cov.55.mean <- MRE(error.infer.clust.cov.100.men.15.25.cov.55.mean)
error.infer.clust.cov.100.women.15.25.cov.55.mean <- as.numeric(vector.mean.AD.num.women.true.cov.100.15.25) - as.numeric(vector.mean.MAR.cov.55.AD.women.cl.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.cov.55.mean <- RMSE(error.infer.clust.cov.100.women.15.25.cov.55.mean)
MAE.error.infer.clust.cov.100.women.15.25.cov.55.mean <- MAE(error.infer.clust.cov.100.women.15.25.cov.55.mean)
ARMSE.error.infer.clust.cov.100.women.15.25.cov.55.mean <- ARMSE(v1=vector.mean.AD.num.women.true.cov.100.15.25, v2=vector.mean.MAR.cov.55.AD.women.cl.15.25)
MRE.error.infer.clust.cov.100.women.15.25.cov.55.mean <- MRE(error.infer.clust.cov.100.women.15.25.cov.55.mean)
# Median
error.infer.clust.cov.100.men.15.25.cov.55.med <- as.numeric(vector.med.AD.num.men.true.cov.100.15.25) - as.numeric(vector.med.MAR.cov.55.AD.men.cl.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.cov.55.med <- RMSE(error.infer.clust.cov.100.men.15.25.cov.55.med)
MAE.error.infer.clust.cov.100.men.15.25.cov.55.med <- MAE(error.infer.clust.cov.100.men.15.25.cov.55.med)
ARMSE.error.infer.clust.cov.100.men.15.25.cov.55 <- ARMSE(v1=vector.med.AD.num.men.true.cov.100.15.25, v2=vector.med.MAR.cov.55.AD.men.cl.15.25)
MRE.error.infer.clust.cov.100.men.15.25.cov.55.med <- MRE(error.infer.clust.cov.100.men.15.25.cov.55.med)
error.infer.clust.cov.100.women.15.25.cov.55.med <- as.numeric(vector.med.AD.num.women.true.cov.100.15.25) - as.numeric(vector.med.MAR.cov.55.AD.women.cl.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.cov.55.med <- RMSE(error.infer.clust.cov.100.women.15.25.cov.55.med)
MAE.error.infer.clust.cov.100.women.15.25.cov.55.med <- MAE(error.infer.clust.cov.100.women.15.25.cov.55.med)
ARMSE.error.infer.clust.cov.100.women.15.25.cov.55.med <- ARMSE(v1=vector.med.AD.num.women.true.cov.100.15.25, v2=vector.med.MAR.cov.55.AD.women.cl.15.25)
MRE.error.infer.clust.cov.100.women.15.25.cov.55.med <- MRE(error.infer.clust.cov.100.women.15.25.cov.55.med)
# Standard deviation
error.infer.clust.cov.100.men.15.25.cov.55.sd <- as.numeric(vector.sd.AD.num.men.true.cov.100.15.25) - as.numeric(vector.sd.MAR.cov.55.AD.men.cl.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.cov.55.sd <- RMSE(error.infer.clust.cov.100.men.15.25.cov.55.sd)
MAE.error.infer.clust.cov.100.men.15.25.cov.55.sd <- MAE(error.infer.clust.cov.100.men.15.25.cov.55.sd)
ARMSE.error.infer.clust.cov.100.men.15.25.cov.55 <- ARMSE(v1=vector.sd.AD.num.men.true.cov.100.15.25, v2=vector.sd.MAR.cov.55.AD.men.cl.15.25)
MRE.error.infer.clust.cov.100.men.15.25.cov.55.sd <- MRE(error.infer.clust.cov.100.men.15.25.cov.55.sd)
error.infer.clust.cov.100.women.15.25.cov.55.sd <- as.numeric(vector.sd.AD.num.women.true.cov.100.15.25) - as.numeric(vector.sd.MAR.cov.55.AD.women.cl.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.cov.55.sd <- RMSE(error.infer.clust.cov.100.women.15.25.cov.55.sd)
MAE.error.infer.clust.cov.100.women.15.25.cov.55.sd <- MAE(error.infer.clust.cov.100.women.15.25.cov.55.sd)
ARMSE.error.infer.clust.cov.100.women.15.25.cov.55.sd <- ARMSE(v1=vector.sd.AD.num.women.true.cov.100.15.25, v2=vector.sd.MAR.cov.55.AD.women.cl.15.25)
MRE.error.infer.clust.cov.100.women.15.25.cov.55.sd <- MRE(error.infer.clust.cov.100.women.15.25.cov.55.sd)
# 25.40
# Mean
error.infer.clust.cov.100.men.25.40.cov.55.mean <- as.numeric(vector.mean.AD.num.men.true.cov.100.25.40) - as.numeric(vector.mean.MAR.cov.55.AD.men.cl.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.cov.55.mean <- RMSE(error.infer.clust.cov.100.men.25.40.cov.55.mean)
MAE.error.infer.clust.cov.100.men.25.40.cov.55.mean <- MAE(error.infer.clust.cov.100.men.25.40.cov.55.mean)
ARMSE.error.infer.clust.cov.100.men.25.40.cov.55 <- ARMSE(v1=vector.mean.AD.num.men.true.cov.100.25.40, v2=vector.mean.MAR.cov.55.AD.men.cl.25.40)
MRE.error.infer.clust.cov.100.men.25.40.cov.55.mean <- MRE(error.infer.clust.cov.100.men.25.40.cov.55.mean)
error.infer.clust.cov.100.women.25.40.cov.55.mean <- as.numeric(vector.mean.AD.num.women.true.cov.100.25.40) - as.numeric(vector.mean.MAR.cov.55.AD.women.cl.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.cov.55.mean <- RMSE(error.infer.clust.cov.100.women.25.40.cov.55.mean)
MAE.error.infer.clust.cov.100.women.25.40.cov.55.mean <- MAE(error.infer.clust.cov.100.women.25.40.cov.55.mean)
ARMSE.error.infer.clust.cov.100.women.25.40.cov.55.mean <- ARMSE(v1=vector.mean.AD.num.women.true.cov.100.25.40, v2=vector.mean.MAR.cov.55.AD.women.cl.25.40)
MRE.error.infer.clust.cov.100.women.25.40.cov.55.mean <- MRE(error.infer.clust.cov.100.women.25.40.cov.55.mean)
# Median
error.infer.clust.cov.100.men.25.40.cov.55.med <- as.numeric(vector.med.AD.num.men.true.cov.100.25.40) - as.numeric(vector.med.MAR.cov.55.AD.men.cl.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.cov.55.med <- RMSE(error.infer.clust.cov.100.men.25.40.cov.55.med)
MAE.error.infer.clust.cov.100.men.25.40.cov.55.med <- MAE(error.infer.clust.cov.100.men.25.40.cov.55.med)
ARMSE.error.infer.clust.cov.100.men.25.40.cov.55 <- ARMSE(v1=vector.med.AD.num.men.true.cov.100.25.40, v2=vector.med.MAR.cov.55.AD.men.cl.25.40)
MRE.error.infer.clust.cov.100.men.25.40.cov.55.med <- MRE(error.infer.clust.cov.100.men.25.40.cov.55.med)
error.infer.clust.cov.100.women.25.40.cov.55.med <- as.numeric(vector.med.AD.num.women.true.cov.100.25.40) - as.numeric(vector.med.MAR.cov.55.AD.women.cl.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.cov.55.med <- RMSE(error.infer.clust.cov.100.women.25.40.cov.55.med)
MAE.error.infer.clust.cov.100.women.25.40.cov.55.med <- MAE(error.infer.clust.cov.100.women.25.40.cov.55.med)
ARMSE.error.infer.clust.cov.100.women.25.40.cov.55.med <- ARMSE(v1=vector.med.AD.num.women.true.cov.100.25.40, v2=vector.med.MAR.cov.55.AD.women.cl.25.40)
MRE.error.infer.clust.cov.100.women.25.40.cov.55.med <- MRE(error.infer.clust.cov.100.women.25.40.cov.55.med)
# Standard deviation
error.infer.clust.cov.100.men.25.40.cov.55.sd <- as.numeric(vector.sd.AD.num.men.true.cov.100.25.40) - as.numeric(vector.sd.MAR.cov.55.AD.men.cl.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.cov.55.sd <- RMSE(error.infer.clust.cov.100.men.25.40.cov.55.sd)
MAE.error.infer.clust.cov.100.men.25.40.cov.55.sd <- MAE(error.infer.clust.cov.100.men.25.40.cov.55.sd)
ARMSE.error.infer.clust.cov.100.men.25.40.cov.55 <- ARMSE(v1=vector.sd.AD.num.men.true.cov.100.25.40, v2=vector.sd.MAR.cov.55.AD.men.cl.25.40)
MRE.error.infer.clust.cov.100.men.25.40.cov.55.sd <- MRE(error.infer.clust.cov.100.men.25.40.cov.55.sd)
error.infer.clust.cov.100.women.25.40.cov.55.sd <- as.numeric(vector.sd.AD.num.women.true.cov.100.25.40) - as.numeric(vector.sd.MAR.cov.55.AD.women.cl.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.cov.55.sd <- RMSE(error.infer.clust.cov.100.women.25.40.cov.55.sd)
MAE.error.infer.clust.cov.100.women.25.40.cov.55.sd <- MAE(error.infer.clust.cov.100.women.25.40.cov.55.sd)
ARMSE.error.infer.clust.cov.100.women.25.40.cov.55.sd <- ARMSE(v1=vector.sd.AD.num.women.true.cov.100.25.40, v2=vector.sd.MAR.cov.55.AD.women.cl.25.40)
MRE.error.infer.clust.cov.100.women.25.40.cov.55.sd <- MRE(error.infer.clust.cov.100.women.25.40.cov.55.sd)
# 40.50
# Mean
error.infer.clust.cov.100.men.40.50.cov.55.mean <- as.numeric(vector.mean.AD.num.men.true.cov.100.40.50) - as.numeric(vector.mean.MAR.cov.55.AD.men.cl.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.cov.55.mean <- RMSE(error.infer.clust.cov.100.men.40.50.cov.55.mean)
MAE.error.infer.clust.cov.100.men.40.50.cov.55.mean <- MAE(error.infer.clust.cov.100.men.40.50.cov.55.mean)
ARMSE.error.infer.clust.cov.100.men.40.50.cov.55 <- ARMSE(v1=vector.mean.AD.num.men.true.cov.100.40.50, v2=vector.mean.MAR.cov.55.AD.men.cl.40.50)
MRE.error.infer.clust.cov.100.men.40.50.cov.55.mean <- MRE(error.infer.clust.cov.100.men.40.50.cov.55.mean)
error.infer.clust.cov.100.women.40.50.cov.55.mean <- as.numeric(vector.mean.AD.num.women.true.cov.100.40.50) - as.numeric(vector.mean.MAR.cov.55.AD.women.cl.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.cov.55.mean <- RMSE(error.infer.clust.cov.100.women.40.50.cov.55.mean)
MAE.error.infer.clust.cov.100.women.40.50.cov.55.mean <- MAE(error.infer.clust.cov.100.women.40.50.cov.55.mean)
ARMSE.error.infer.clust.cov.100.women.40.50.cov.55.mean <- ARMSE(v1=vector.mean.AD.num.women.true.cov.100.40.50, v2=vector.mean.MAR.cov.55.AD.women.cl.40.50)
MRE.error.infer.clust.cov.100.women.40.50.cov.55.mean <- MRE(error.infer.clust.cov.100.women.40.50.cov.55.mean)
# Median
error.infer.clust.cov.100.men.40.50.cov.55.med <- as.numeric(vector.med.AD.num.men.true.cov.100.40.50) - as.numeric(vector.med.MAR.cov.55.AD.men.cl.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.cov.55.med <- RMSE(error.infer.clust.cov.100.men.40.50.cov.55.med)
MAE.error.infer.clust.cov.100.men.40.50.cov.55.med <- MAE(error.infer.clust.cov.100.men.40.50.cov.55.med)
ARMSE.error.infer.clust.cov.100.men.40.50.cov.55 <- ARMSE(v1=vector.med.AD.num.men.true.cov.100.40.50, v2=vector.med.MAR.cov.55.AD.men.cl.40.50)
MRE.error.infer.clust.cov.100.men.40.50.cov.55.med <- MRE(error.infer.clust.cov.100.men.40.50.cov.55.med)
error.infer.clust.cov.100.women.40.50.cov.55.med <- as.numeric(vector.med.AD.num.women.true.cov.100.40.50) - as.numeric(vector.med.MAR.cov.55.AD.women.cl.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.cov.55.med <- RMSE(error.infer.clust.cov.100.women.40.50.cov.55.med)
MAE.error.infer.clust.cov.100.women.40.50.cov.55.med <- MAE(error.infer.clust.cov.100.women.40.50.cov.55.med)
ARMSE.error.infer.clust.cov.100.women.40.50.cov.55.med <- ARMSE(v1=vector.med.AD.num.women.true.cov.100.40.50, v2=vector.med.MAR.cov.55.AD.women.cl.40.50)
MRE.error.infer.clust.cov.100.women.40.50.cov.55.med <- MRE(error.infer.clust.cov.100.women.40.50.cov.55.med)
# Standard deviation
error.infer.clust.cov.100.men.40.50.cov.55.sd <- as.numeric(vector.sd.AD.num.men.true.cov.100.40.50) - as.numeric(vector.sd.MAR.cov.55.AD.men.cl.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.cov.55.sd <- RMSE(error.infer.clust.cov.100.men.40.50.cov.55.sd)
MAE.error.infer.clust.cov.100.men.40.50.cov.55.sd <- MAE(error.infer.clust.cov.100.men.40.50.cov.55.sd)
ARMSE.error.infer.clust.cov.100.men.40.50.cov.55 <- ARMSE(v1=vector.sd.AD.num.men.true.cov.100.40.50, v2=vector.sd.MAR.cov.55.AD.men.cl.40.50)
MRE.error.infer.clust.cov.100.men.40.50.cov.55.sd <- MRE(error.infer.clust.cov.100.men.40.50.cov.55.sd)
error.infer.clust.cov.100.women.40.50.cov.55.sd <- as.numeric(vector.sd.AD.num.women.true.cov.100.40.50) - as.numeric(vector.sd.MAR.cov.55.AD.women.cl.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.cov.55.sd <- RMSE(error.infer.clust.cov.100.women.40.50.cov.55.sd)
MAE.error.infer.clust.cov.100.women.40.50.cov.55.sd <- MAE(error.infer.clust.cov.100.women.40.50.cov.55.sd)
ARMSE.error.infer.clust.cov.100.women.40.50.cov.55.sd <- ARMSE(v1=vector.sd.AD.num.women.true.cov.100.40.50, v2=vector.sd.MAR.cov.55.AD.women.cl.40.50)
MRE.error.infer.clust.cov.100.women.40.50.cov.55.sd <- MRE(error.infer.clust.cov.100.women.40.50.cov.55.sd)
# Cov 60
# 15.25
# Mean
error.infer.clust.cov.100.men.15.25.cov.60.mean <- as.numeric(vector.mean.AD.num.men.true.cov.100.15.25) - as.numeric(vector.mean.MAR.cov.60.AD.men.cl.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.cov.60.mean <- RMSE(error.infer.clust.cov.100.men.15.25.cov.60.mean)
MAE.error.infer.clust.cov.100.men.15.25.cov.60.mean <- MAE(error.infer.clust.cov.100.men.15.25.cov.60.mean)
ARMSE.error.infer.clust.cov.100.men.15.25.cov.60 <- ARMSE(v1=vector.mean.AD.num.men.true.cov.100.15.25, v2=vector.mean.MAR.cov.60.AD.men.cl.15.25)
MRE.error.infer.clust.cov.100.men.15.25.cov.60.mean <- MRE(error.infer.clust.cov.100.men.15.25.cov.60.mean)
error.infer.clust.cov.100.women.15.25.cov.60.mean <- as.numeric(vector.mean.AD.num.women.true.cov.100.15.25) - as.numeric(vector.mean.MAR.cov.60.AD.women.cl.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.cov.60.mean <- RMSE(error.infer.clust.cov.100.women.15.25.cov.60.mean)
MAE.error.infer.clust.cov.100.women.15.25.cov.60.mean <- MAE(error.infer.clust.cov.100.women.15.25.cov.60.mean)
ARMSE.error.infer.clust.cov.100.women.15.25.cov.60.mean <- ARMSE(v1=vector.mean.AD.num.women.true.cov.100.15.25, v2=vector.mean.MAR.cov.60.AD.women.cl.15.25)
MRE.error.infer.clust.cov.100.women.15.25.cov.60.mean <- MRE(error.infer.clust.cov.100.women.15.25.cov.60.mean)
# Median
error.infer.clust.cov.100.men.15.25.cov.60.med <- as.numeric(vector.med.AD.num.men.true.cov.100.15.25) - as.numeric(vector.med.MAR.cov.60.AD.men.cl.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.cov.60.med <- RMSE(error.infer.clust.cov.100.men.15.25.cov.60.med)
MAE.error.infer.clust.cov.100.men.15.25.cov.60.med <- MAE(error.infer.clust.cov.100.men.15.25.cov.60.med)
ARMSE.error.infer.clust.cov.100.men.15.25.cov.60 <- ARMSE(v1=vector.med.AD.num.men.true.cov.100.15.25, v2=vector.med.MAR.cov.60.AD.men.cl.15.25)
MRE.error.infer.clust.cov.100.men.15.25.cov.60.med <- MRE(error.infer.clust.cov.100.men.15.25.cov.60.med)
error.infer.clust.cov.100.women.15.25.cov.60.med <- as.numeric(vector.med.AD.num.women.true.cov.100.15.25) - as.numeric(vector.med.MAR.cov.60.AD.women.cl.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.cov.60.med <- RMSE(error.infer.clust.cov.100.women.15.25.cov.60.med)
MAE.error.infer.clust.cov.100.women.15.25.cov.60.med <- MAE(error.infer.clust.cov.100.women.15.25.cov.60.med)
ARMSE.error.infer.clust.cov.100.women.15.25.cov.60.med <- ARMSE(v1=vector.med.AD.num.women.true.cov.100.15.25, v2=vector.med.MAR.cov.60.AD.women.cl.15.25)
MRE.error.infer.clust.cov.100.women.15.25.cov.60.med <- MRE(error.infer.clust.cov.100.women.15.25.cov.60.med)
# Standard deviation
error.infer.clust.cov.100.men.15.25.cov.60.sd <- as.numeric(vector.sd.AD.num.men.true.cov.100.15.25) - as.numeric(vector.sd.MAR.cov.60.AD.men.cl.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.cov.60.sd <- RMSE(error.infer.clust.cov.100.men.15.25.cov.60.sd)
MAE.error.infer.clust.cov.100.men.15.25.cov.60.sd <- MAE(error.infer.clust.cov.100.men.15.25.cov.60.sd)
ARMSE.error.infer.clust.cov.100.men.15.25.cov.60 <- ARMSE(v1=vector.sd.AD.num.men.true.cov.100.15.25, v2=vector.sd.MAR.cov.60.AD.men.cl.15.25)
MRE.error.infer.clust.cov.100.men.15.25.cov.60.sd <- MRE(error.infer.clust.cov.100.men.15.25.cov.60.sd)
error.infer.clust.cov.100.women.15.25.cov.60.sd <- as.numeric(vector.sd.AD.num.women.true.cov.100.15.25) - as.numeric(vector.sd.MAR.cov.60.AD.women.cl.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.cov.60.sd <- RMSE(error.infer.clust.cov.100.women.15.25.cov.60.sd)
MAE.error.infer.clust.cov.100.women.15.25.cov.60.sd <- MAE(error.infer.clust.cov.100.women.15.25.cov.60.sd)
ARMSE.error.infer.clust.cov.100.women.15.25.cov.60.sd <- ARMSE(v1=vector.sd.AD.num.women.true.cov.100.15.25, v2=vector.sd.MAR.cov.60.AD.women.cl.15.25)
MRE.error.infer.clust.cov.100.women.15.25.cov.60.sd <- MRE(error.infer.clust.cov.100.women.15.25.cov.60.sd)
# 25.40
# Mean
error.infer.clust.cov.100.men.25.40.cov.60.mean <- as.numeric(vector.mean.AD.num.men.true.cov.100.25.40) - as.numeric(vector.mean.MAR.cov.60.AD.men.cl.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.cov.60.mean <- RMSE(error.infer.clust.cov.100.men.25.40.cov.60.mean)
MAE.error.infer.clust.cov.100.men.25.40.cov.60.mean <- MAE(error.infer.clust.cov.100.men.25.40.cov.60.mean)
ARMSE.error.infer.clust.cov.100.men.25.40.cov.60 <- ARMSE(v1=vector.mean.AD.num.men.true.cov.100.25.40, v2=vector.mean.MAR.cov.60.AD.men.cl.25.40)
MRE.error.infer.clust.cov.100.men.25.40.cov.60.mean <- MRE(error.infer.clust.cov.100.men.25.40.cov.60.mean)
error.infer.clust.cov.100.women.25.40.cov.60.mean <- as.numeric(vector.mean.AD.num.women.true.cov.100.25.40) - as.numeric(vector.mean.MAR.cov.60.AD.women.cl.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.cov.60.mean <- RMSE(error.infer.clust.cov.100.women.25.40.cov.60.mean)
MAE.error.infer.clust.cov.100.women.25.40.cov.60.mean <- MAE(error.infer.clust.cov.100.women.25.40.cov.60.mean)
ARMSE.error.infer.clust.cov.100.women.25.40.cov.60.mean <- ARMSE(v1=vector.mean.AD.num.women.true.cov.100.25.40, v2=vector.mean.MAR.cov.60.AD.women.cl.25.40)
MRE.error.infer.clust.cov.100.women.25.40.cov.60.mean <- MRE(error.infer.clust.cov.100.women.25.40.cov.60.mean)
# Median
error.infer.clust.cov.100.men.25.40.cov.60.med <- as.numeric(vector.med.AD.num.men.true.cov.100.25.40) - as.numeric(vector.med.MAR.cov.60.AD.men.cl.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.cov.60.med <- RMSE(error.infer.clust.cov.100.men.25.40.cov.60.med)
MAE.error.infer.clust.cov.100.men.25.40.cov.60.med <- MAE(error.infer.clust.cov.100.men.25.40.cov.60.med)
ARMSE.error.infer.clust.cov.100.men.25.40.cov.60 <- ARMSE(v1=vector.med.AD.num.men.true.cov.100.25.40, v2=vector.med.MAR.cov.60.AD.men.cl.25.40)
MRE.error.infer.clust.cov.100.men.25.40.cov.60.med <- MRE(error.infer.clust.cov.100.men.25.40.cov.60.med)
error.infer.clust.cov.100.women.25.40.cov.60.med <- as.numeric(vector.med.AD.num.women.true.cov.100.25.40) - as.numeric(vector.med.MAR.cov.60.AD.women.cl.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.cov.60.med <- RMSE(error.infer.clust.cov.100.women.25.40.cov.60.med)
MAE.error.infer.clust.cov.100.women.25.40.cov.60.med <- MAE(error.infer.clust.cov.100.women.25.40.cov.60.med)
ARMSE.error.infer.clust.cov.100.women.25.40.cov.60.med <- ARMSE(v1=vector.med.AD.num.women.true.cov.100.25.40, v2=vector.med.MAR.cov.60.AD.women.cl.25.40)
MRE.error.infer.clust.cov.100.women.25.40.cov.60.med <- MRE(error.infer.clust.cov.100.women.25.40.cov.60.med)
# Standard deviation
error.infer.clust.cov.100.men.25.40.cov.60.sd <- as.numeric(vector.sd.AD.num.men.true.cov.100.25.40) - as.numeric(vector.sd.MAR.cov.60.AD.men.cl.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.cov.60.sd <- RMSE(error.infer.clust.cov.100.men.25.40.cov.60.sd)
MAE.error.infer.clust.cov.100.men.25.40.cov.60.sd <- MAE(error.infer.clust.cov.100.men.25.40.cov.60.sd)
ARMSE.error.infer.clust.cov.100.men.25.40.cov.60 <- ARMSE(v1=vector.sd.AD.num.men.true.cov.100.25.40, v2=vector.sd.MAR.cov.60.AD.men.cl.25.40)
MRE.error.infer.clust.cov.100.men.25.40.cov.60.sd <- MRE(error.infer.clust.cov.100.men.25.40.cov.60.sd)
error.infer.clust.cov.100.women.25.40.cov.60.sd <- as.numeric(vector.sd.AD.num.women.true.cov.100.25.40) - as.numeric(vector.sd.MAR.cov.60.AD.women.cl.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.cov.60.sd <- RMSE(error.infer.clust.cov.100.women.25.40.cov.60.sd)
MAE.error.infer.clust.cov.100.women.25.40.cov.60.sd <- MAE(error.infer.clust.cov.100.women.25.40.cov.60.sd)
ARMSE.error.infer.clust.cov.100.women.25.40.cov.60.sd <- ARMSE(v1=vector.sd.AD.num.women.true.cov.100.25.40, v2=vector.sd.MAR.cov.60.AD.women.cl.25.40)
MRE.error.infer.clust.cov.100.women.25.40.cov.60.sd <- MRE(error.infer.clust.cov.100.women.25.40.cov.60.sd)
# 40.50
# Mean
error.infer.clust.cov.100.men.40.50.cov.60.mean <- as.numeric(vector.mean.AD.num.men.true.cov.100.40.50) - as.numeric(vector.mean.MAR.cov.60.AD.men.cl.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.cov.60.mean <- RMSE(error.infer.clust.cov.100.men.40.50.cov.60.mean)
MAE.error.infer.clust.cov.100.men.40.50.cov.60.mean <- MAE(error.infer.clust.cov.100.men.40.50.cov.60.mean)
ARMSE.error.infer.clust.cov.100.men.40.50.cov.60 <- ARMSE(v1=vector.mean.AD.num.men.true.cov.100.40.50, v2=vector.mean.MAR.cov.60.AD.men.cl.40.50)
MRE.error.infer.clust.cov.100.men.40.50.cov.60.mean <- MRE(error.infer.clust.cov.100.men.40.50.cov.60.mean)
error.infer.clust.cov.100.women.40.50.cov.60.mean <- as.numeric(vector.mean.AD.num.women.true.cov.100.40.50) - as.numeric(vector.mean.MAR.cov.60.AD.women.cl.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.cov.60.mean <- RMSE(error.infer.clust.cov.100.women.40.50.cov.60.mean)
MAE.error.infer.clust.cov.100.women.40.50.cov.60.mean <- MAE(error.infer.clust.cov.100.women.40.50.cov.60.mean)
ARMSE.error.infer.clust.cov.100.women.40.50.cov.60.mean <- ARMSE(v1=vector.mean.AD.num.women.true.cov.100.40.50, v2=vector.mean.MAR.cov.60.AD.women.cl.40.50)
MRE.error.infer.clust.cov.100.women.40.50.cov.60.mean <- MRE(error.infer.clust.cov.100.women.40.50.cov.60.mean)
# Median
error.infer.clust.cov.100.men.40.50.cov.60.med <- as.numeric(vector.med.AD.num.men.true.cov.100.40.50) - as.numeric(vector.med.MAR.cov.60.AD.men.cl.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.cov.60.med <- RMSE(error.infer.clust.cov.100.men.40.50.cov.60.med)
MAE.error.infer.clust.cov.100.men.40.50.cov.60.med <- MAE(error.infer.clust.cov.100.men.40.50.cov.60.med)
ARMSE.error.infer.clust.cov.100.men.40.50.cov.60 <- ARMSE(v1=vector.med.AD.num.men.true.cov.100.40.50, v2=vector.med.MAR.cov.60.AD.men.cl.40.50)
MRE.error.infer.clust.cov.100.men.40.50.cov.60.med <- MRE(error.infer.clust.cov.100.men.40.50.cov.60.med)
error.infer.clust.cov.100.women.40.50.cov.60.med <- as.numeric(vector.med.AD.num.women.true.cov.100.40.50) - as.numeric(vector.med.MAR.cov.60.AD.women.cl.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.cov.60.med <- RMSE(error.infer.clust.cov.100.women.40.50.cov.60.med)
MAE.error.infer.clust.cov.100.women.40.50.cov.60.med <- MAE(error.infer.clust.cov.100.women.40.50.cov.60.med)
ARMSE.error.infer.clust.cov.100.women.40.50.cov.60.med <- ARMSE(v1=vector.med.AD.num.women.true.cov.100.40.50, v2=vector.med.MAR.cov.60.AD.women.cl.40.50)
MRE.error.infer.clust.cov.100.women.40.50.cov.60.med <- MRE(error.infer.clust.cov.100.women.40.50.cov.60.med)
# Standard deviation
error.infer.clust.cov.100.men.40.50.cov.60.sd <- as.numeric(vector.sd.AD.num.men.true.cov.100.40.50) - as.numeric(vector.sd.MAR.cov.60.AD.men.cl.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.cov.60.sd <- RMSE(error.infer.clust.cov.100.men.40.50.cov.60.sd)
MAE.error.infer.clust.cov.100.men.40.50.cov.60.sd <- MAE(error.infer.clust.cov.100.men.40.50.cov.60.sd)
ARMSE.error.infer.clust.cov.100.men.40.50.cov.60 <- ARMSE(v1=vector.sd.AD.num.men.true.cov.100.40.50, v2=vector.sd.MAR.cov.60.AD.men.cl.40.50)
MRE.error.infer.clust.cov.100.men.40.50.cov.60.sd <- MRE(error.infer.clust.cov.100.men.40.50.cov.60.sd)
error.infer.clust.cov.100.women.40.50.cov.60.sd <- as.numeric(vector.sd.AD.num.women.true.cov.100.40.50) - as.numeric(vector.sd.MAR.cov.60.AD.women.cl.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.cov.60.sd <- RMSE(error.infer.clust.cov.100.women.40.50.cov.60.sd)
MAE.error.infer.clust.cov.100.women.40.50.cov.60.sd <- MAE(error.infer.clust.cov.100.women.40.50.cov.60.sd)
ARMSE.error.infer.clust.cov.100.women.40.50.cov.60.sd <- ARMSE(v1=vector.sd.AD.num.women.true.cov.100.40.50, v2=vector.sd.MAR.cov.60.AD.women.cl.40.50)
MRE.error.infer.clust.cov.100.women.40.50.cov.60.sd <- MRE(error.infer.clust.cov.100.women.40.50.cov.60.sd)
# Cov 65
# 15.25
# Mean
error.infer.clust.cov.100.men.15.25.cov.65.mean <- as.numeric(vector.mean.AD.num.men.true.cov.100.15.25) - as.numeric(vector.mean.MAR.cov.65.AD.men.cl.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.cov.65.mean <- RMSE(error.infer.clust.cov.100.men.15.25.cov.65.mean)
MAE.error.infer.clust.cov.100.men.15.25.cov.65.mean <- MAE(error.infer.clust.cov.100.men.15.25.cov.65.mean)
ARMSE.error.infer.clust.cov.100.men.15.25.cov.65 <- ARMSE(v1=vector.mean.AD.num.men.true.cov.100.15.25, v2=vector.mean.MAR.cov.65.AD.men.cl.15.25)
MRE.error.infer.clust.cov.100.men.15.25.cov.65.mean <- MRE(error.infer.clust.cov.100.men.15.25.cov.65.mean)
error.infer.clust.cov.100.women.15.25.cov.65.mean <- as.numeric(vector.mean.AD.num.women.true.cov.100.15.25) - as.numeric(vector.mean.MAR.cov.65.AD.women.cl.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.cov.65.mean <- RMSE(error.infer.clust.cov.100.women.15.25.cov.65.mean)
MAE.error.infer.clust.cov.100.women.15.25.cov.65.mean <- MAE(error.infer.clust.cov.100.women.15.25.cov.65.mean)
ARMSE.error.infer.clust.cov.100.women.15.25.cov.65.mean <- ARMSE(v1=vector.mean.AD.num.women.true.cov.100.15.25, v2=vector.mean.MAR.cov.65.AD.women.cl.15.25)
MRE.error.infer.clust.cov.100.women.15.25.cov.65.mean <- MRE(error.infer.clust.cov.100.women.15.25.cov.65.mean)
# Median
error.infer.clust.cov.100.men.15.25.cov.65.med <- as.numeric(vector.med.AD.num.men.true.cov.100.15.25) - as.numeric(vector.med.MAR.cov.65.AD.men.cl.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.cov.65.med <- RMSE(error.infer.clust.cov.100.men.15.25.cov.65.med)
MAE.error.infer.clust.cov.100.men.15.25.cov.65.med <- MAE(error.infer.clust.cov.100.men.15.25.cov.65.med)
ARMSE.error.infer.clust.cov.100.men.15.25.cov.65 <- ARMSE(v1=vector.med.AD.num.men.true.cov.100.15.25, v2=vector.med.MAR.cov.65.AD.men.cl.15.25)
MRE.error.infer.clust.cov.100.men.15.25.cov.65.med <- MRE(error.infer.clust.cov.100.men.15.25.cov.65.med)
error.infer.clust.cov.100.women.15.25.cov.65.med <- as.numeric(vector.med.AD.num.women.true.cov.100.15.25) - as.numeric(vector.med.MAR.cov.65.AD.women.cl.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.cov.65.med <- RMSE(error.infer.clust.cov.100.women.15.25.cov.65.med)
MAE.error.infer.clust.cov.100.women.15.25.cov.65.med <- MAE(error.infer.clust.cov.100.women.15.25.cov.65.med)
ARMSE.error.infer.clust.cov.100.women.15.25.cov.65.med <- ARMSE(v1=vector.med.AD.num.women.true.cov.100.15.25, v2=vector.med.MAR.cov.65.AD.women.cl.15.25)
MRE.error.infer.clust.cov.100.women.15.25.cov.65.med <- MRE(error.infer.clust.cov.100.women.15.25.cov.65.med)
# Standard deviation
error.infer.clust.cov.100.men.15.25.cov.65.sd <- as.numeric(vector.sd.AD.num.men.true.cov.100.15.25) - as.numeric(vector.sd.MAR.cov.65.AD.men.cl.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.cov.65.sd <- RMSE(error.infer.clust.cov.100.men.15.25.cov.65.sd)
MAE.error.infer.clust.cov.100.men.15.25.cov.65.sd <- MAE(error.infer.clust.cov.100.men.15.25.cov.65.sd)
ARMSE.error.infer.clust.cov.100.men.15.25.cov.65 <- ARMSE(v1=vector.sd.AD.num.men.true.cov.100.15.25, v2=vector.sd.MAR.cov.65.AD.men.cl.15.25)
MRE.error.infer.clust.cov.100.men.15.25.cov.65.sd <- MRE(error.infer.clust.cov.100.men.15.25.cov.65.sd)
error.infer.clust.cov.100.women.15.25.cov.65.sd <- as.numeric(vector.sd.AD.num.women.true.cov.100.15.25) - as.numeric(vector.sd.MAR.cov.65.AD.women.cl.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.cov.65.sd <- RMSE(error.infer.clust.cov.100.women.15.25.cov.65.sd)
MAE.error.infer.clust.cov.100.women.15.25.cov.65.sd <- MAE(error.infer.clust.cov.100.women.15.25.cov.65.sd)
ARMSE.error.infer.clust.cov.100.women.15.25.cov.65.sd <- ARMSE(v1=vector.sd.AD.num.women.true.cov.100.15.25, v2=vector.sd.MAR.cov.65.AD.women.cl.15.25)
MRE.error.infer.clust.cov.100.women.15.25.cov.65.sd <- MRE(error.infer.clust.cov.100.women.15.25.cov.65.sd)
# 25.40
# Mean
error.infer.clust.cov.100.men.25.40.cov.65.mean <- as.numeric(vector.mean.AD.num.men.true.cov.100.25.40) - as.numeric(vector.mean.MAR.cov.65.AD.men.cl.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.cov.65.mean <- RMSE(error.infer.clust.cov.100.men.25.40.cov.65.mean)
MAE.error.infer.clust.cov.100.men.25.40.cov.65.mean <- MAE(error.infer.clust.cov.100.men.25.40.cov.65.mean)
ARMSE.error.infer.clust.cov.100.men.25.40.cov.65 <- ARMSE(v1=vector.mean.AD.num.men.true.cov.100.25.40, v2=vector.mean.MAR.cov.65.AD.men.cl.25.40)
MRE.error.infer.clust.cov.100.men.25.40.cov.65.mean <- MRE(error.infer.clust.cov.100.men.25.40.cov.65.mean)
error.infer.clust.cov.100.women.25.40.cov.65.mean <- as.numeric(vector.mean.AD.num.women.true.cov.100.25.40) - as.numeric(vector.mean.MAR.cov.65.AD.women.cl.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.cov.65.mean <- RMSE(error.infer.clust.cov.100.women.25.40.cov.65.mean)
MAE.error.infer.clust.cov.100.women.25.40.cov.65.mean <- MAE(error.infer.clust.cov.100.women.25.40.cov.65.mean)
ARMSE.error.infer.clust.cov.100.women.25.40.cov.65.mean <- ARMSE(v1=vector.mean.AD.num.women.true.cov.100.25.40, v2=vector.mean.MAR.cov.65.AD.women.cl.25.40)
MRE.error.infer.clust.cov.100.women.25.40.cov.65.mean <- MRE(error.infer.clust.cov.100.women.25.40.cov.65.mean)
# Median
error.infer.clust.cov.100.men.25.40.cov.65.med <- as.numeric(vector.med.AD.num.men.true.cov.100.25.40) - as.numeric(vector.med.MAR.cov.65.AD.men.cl.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.cov.65.med <- RMSE(error.infer.clust.cov.100.men.25.40.cov.65.med)
MAE.error.infer.clust.cov.100.men.25.40.cov.65.med <- MAE(error.infer.clust.cov.100.men.25.40.cov.65.med)
ARMSE.error.infer.clust.cov.100.men.25.40.cov.65 <- ARMSE(v1=vector.med.AD.num.men.true.cov.100.25.40, v2=vector.med.MAR.cov.65.AD.men.cl.25.40)
MRE.error.infer.clust.cov.100.men.25.40.cov.65.med <- MRE(error.infer.clust.cov.100.men.25.40.cov.65.med)
error.infer.clust.cov.100.women.25.40.cov.65.med <- as.numeric(vector.med.AD.num.women.true.cov.100.25.40) - as.numeric(vector.med.MAR.cov.65.AD.women.cl.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.cov.65.med <- RMSE(error.infer.clust.cov.100.women.25.40.cov.65.med)
MAE.error.infer.clust.cov.100.women.25.40.cov.65.med <- MAE(error.infer.clust.cov.100.women.25.40.cov.65.med)
ARMSE.error.infer.clust.cov.100.women.25.40.cov.65.med <- ARMSE(v1=vector.med.AD.num.women.true.cov.100.25.40, v2=vector.med.MAR.cov.65.AD.women.cl.25.40)
MRE.error.infer.clust.cov.100.women.25.40.cov.65.med <- MRE(error.infer.clust.cov.100.women.25.40.cov.65.med)
# Standard deviation
error.infer.clust.cov.100.men.25.40.cov.65.sd <- as.numeric(vector.sd.AD.num.men.true.cov.100.25.40) - as.numeric(vector.sd.MAR.cov.65.AD.men.cl.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.cov.65.sd <- RMSE(error.infer.clust.cov.100.men.25.40.cov.65.sd)
MAE.error.infer.clust.cov.100.men.25.40.cov.65.sd <- MAE(error.infer.clust.cov.100.men.25.40.cov.65.sd)
ARMSE.error.infer.clust.cov.100.men.25.40.cov.65 <- ARMSE(v1=vector.sd.AD.num.men.true.cov.100.25.40, v2=vector.sd.MAR.cov.65.AD.men.cl.25.40)
MRE.error.infer.clust.cov.100.men.25.40.cov.65.sd <- MRE(error.infer.clust.cov.100.men.25.40.cov.65.sd)
error.infer.clust.cov.100.women.25.40.cov.65.sd <- as.numeric(vector.sd.AD.num.women.true.cov.100.25.40) - as.numeric(vector.sd.MAR.cov.65.AD.women.cl.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.cov.65.sd <- RMSE(error.infer.clust.cov.100.women.25.40.cov.65.sd)
MAE.error.infer.clust.cov.100.women.25.40.cov.65.sd <- MAE(error.infer.clust.cov.100.women.25.40.cov.65.sd)
ARMSE.error.infer.clust.cov.100.women.25.40.cov.65.sd <- ARMSE(v1=vector.sd.AD.num.women.true.cov.100.25.40, v2=vector.sd.MAR.cov.65.AD.women.cl.25.40)
MRE.error.infer.clust.cov.100.women.25.40.cov.65.sd <- MRE(error.infer.clust.cov.100.women.25.40.cov.65.sd)
# 40.50
# Mean
error.infer.clust.cov.100.men.40.50.cov.65.mean <- as.numeric(vector.mean.AD.num.men.true.cov.100.40.50) - as.numeric(vector.mean.MAR.cov.65.AD.men.cl.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.cov.65.mean <- RMSE(error.infer.clust.cov.100.men.40.50.cov.65.mean)
MAE.error.infer.clust.cov.100.men.40.50.cov.65.mean <- MAE(error.infer.clust.cov.100.men.40.50.cov.65.mean)
ARMSE.error.infer.clust.cov.100.men.40.50.cov.65 <- ARMSE(v1=vector.mean.AD.num.men.true.cov.100.40.50, v2=vector.mean.MAR.cov.65.AD.men.cl.40.50)
MRE.error.infer.clust.cov.100.men.40.50.cov.65.mean <- MRE(error.infer.clust.cov.100.men.40.50.cov.65.mean)
error.infer.clust.cov.100.women.40.50.cov.65.mean <- as.numeric(vector.mean.AD.num.women.true.cov.100.40.50) - as.numeric(vector.mean.MAR.cov.65.AD.women.cl.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.cov.65.mean <- RMSE(error.infer.clust.cov.100.women.40.50.cov.65.mean)
MAE.error.infer.clust.cov.100.women.40.50.cov.65.mean <- MAE(error.infer.clust.cov.100.women.40.50.cov.65.mean)
ARMSE.error.infer.clust.cov.100.women.40.50.cov.65.mean <- ARMSE(v1=vector.mean.AD.num.women.true.cov.100.40.50, v2=vector.mean.MAR.cov.65.AD.women.cl.40.50)
MRE.error.infer.clust.cov.100.women.40.50.cov.65.mean <- MRE(error.infer.clust.cov.100.women.40.50.cov.65.mean)
# Median
error.infer.clust.cov.100.men.40.50.cov.65.med <- as.numeric(vector.med.AD.num.men.true.cov.100.40.50) - as.numeric(vector.med.MAR.cov.65.AD.men.cl.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.cov.65.med <- RMSE(error.infer.clust.cov.100.men.40.50.cov.65.med)
MAE.error.infer.clust.cov.100.men.40.50.cov.65.med <- MAE(error.infer.clust.cov.100.men.40.50.cov.65.med)
ARMSE.error.infer.clust.cov.100.men.40.50.cov.65 <- ARMSE(v1=vector.med.AD.num.men.true.cov.100.40.50, v2=vector.med.MAR.cov.65.AD.men.cl.40.50)
MRE.error.infer.clust.cov.100.men.40.50.cov.65.med <- MRE(error.infer.clust.cov.100.men.40.50.cov.65.med)
error.infer.clust.cov.100.women.40.50.cov.65.med <- as.numeric(vector.med.AD.num.women.true.cov.100.40.50) - as.numeric(vector.med.MAR.cov.65.AD.women.cl.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.cov.65.med <- RMSE(error.infer.clust.cov.100.women.40.50.cov.65.med)
MAE.error.infer.clust.cov.100.women.40.50.cov.65.med <- MAE(error.infer.clust.cov.100.women.40.50.cov.65.med)
ARMSE.error.infer.clust.cov.100.women.40.50.cov.65.med <- ARMSE(v1=vector.med.AD.num.women.true.cov.100.40.50, v2=vector.med.MAR.cov.65.AD.women.cl.40.50)
MRE.error.infer.clust.cov.100.women.40.50.cov.65.med <- MRE(error.infer.clust.cov.100.women.40.50.cov.65.med)
# Standard deviation
error.infer.clust.cov.100.men.40.50.cov.65.sd <- as.numeric(vector.sd.AD.num.men.true.cov.100.40.50) - as.numeric(vector.sd.MAR.cov.65.AD.men.cl.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.cov.65.sd <- RMSE(error.infer.clust.cov.100.men.40.50.cov.65.sd)
MAE.error.infer.clust.cov.100.men.40.50.cov.65.sd <- MAE(error.infer.clust.cov.100.men.40.50.cov.65.sd)
ARMSE.error.infer.clust.cov.100.men.40.50.cov.65 <- ARMSE(v1=vector.sd.AD.num.men.true.cov.100.40.50, v2=vector.sd.MAR.cov.65.AD.men.cl.40.50)
MRE.error.infer.clust.cov.100.men.40.50.cov.65.sd <- MRE(error.infer.clust.cov.100.men.40.50.cov.65.sd)
error.infer.clust.cov.100.women.40.50.cov.65.sd <- as.numeric(vector.sd.AD.num.women.true.cov.100.40.50) - as.numeric(vector.sd.MAR.cov.65.AD.women.cl.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.cov.65.sd <- RMSE(error.infer.clust.cov.100.women.40.50.cov.65.sd)
MAE.error.infer.clust.cov.100.women.40.50.cov.65.sd <- MAE(error.infer.clust.cov.100.women.40.50.cov.65.sd)
ARMSE.error.infer.clust.cov.100.women.40.50.cov.65.sd <- ARMSE(v1=vector.sd.AD.num.women.true.cov.100.40.50, v2=vector.sd.MAR.cov.65.AD.women.cl.40.50)
MRE.error.infer.clust.cov.100.women.40.50.cov.65.sd <- MRE(error.infer.clust.cov.100.women.40.50.cov.65.sd)
# Cov 70
# 15.25
# Mean
error.infer.clust.cov.100.men.15.25.cov.70.mean <- as.numeric(vector.mean.AD.num.men.true.cov.100.15.25) - as.numeric(vector.mean.MAR.cov.70.AD.men.cl.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.cov.70.mean <- RMSE(error.infer.clust.cov.100.men.15.25.cov.70.mean)
MAE.error.infer.clust.cov.100.men.15.25.cov.70.mean <- MAE(error.infer.clust.cov.100.men.15.25.cov.70.mean)
ARMSE.error.infer.clust.cov.100.men.15.25.cov.70 <- ARMSE(v1=vector.mean.AD.num.men.true.cov.100.15.25, v2=vector.mean.MAR.cov.70.AD.men.cl.15.25)
MRE.error.infer.clust.cov.100.men.15.25.cov.70.mean <- MRE(error.infer.clust.cov.100.men.15.25.cov.70.mean)
error.infer.clust.cov.100.women.15.25.cov.70.mean <- as.numeric(vector.mean.AD.num.women.true.cov.100.15.25) - as.numeric(vector.mean.MAR.cov.70.AD.women.cl.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.cov.70.mean <- RMSE(error.infer.clust.cov.100.women.15.25.cov.70.mean)
MAE.error.infer.clust.cov.100.women.15.25.cov.70.mean <- MAE(error.infer.clust.cov.100.women.15.25.cov.70.mean)
ARMSE.error.infer.clust.cov.100.women.15.25.cov.70.mean <- ARMSE(v1=vector.mean.AD.num.women.true.cov.100.15.25, v2=vector.mean.MAR.cov.70.AD.women.cl.15.25)
MRE.error.infer.clust.cov.100.women.15.25.cov.70.mean <- MRE(error.infer.clust.cov.100.women.15.25.cov.70.mean)
# Median
error.infer.clust.cov.100.men.15.25.cov.70.med <- as.numeric(vector.med.AD.num.men.true.cov.100.15.25) - as.numeric(vector.med.MAR.cov.70.AD.men.cl.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.cov.70.med <- RMSE(error.infer.clust.cov.100.men.15.25.cov.70.med)
MAE.error.infer.clust.cov.100.men.15.25.cov.70.med <- MAE(error.infer.clust.cov.100.men.15.25.cov.70.med)
ARMSE.error.infer.clust.cov.100.men.15.25.cov.70 <- ARMSE(v1=vector.med.AD.num.men.true.cov.100.15.25, v2=vector.med.MAR.cov.70.AD.men.cl.15.25)
MRE.error.infer.clust.cov.100.men.15.25.cov.70.med <- MRE(error.infer.clust.cov.100.men.15.25.cov.70.med)
error.infer.clust.cov.100.women.15.25.cov.70.med <- as.numeric(vector.med.AD.num.women.true.cov.100.15.25) - as.numeric(vector.med.MAR.cov.70.AD.women.cl.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.cov.70.med <- RMSE(error.infer.clust.cov.100.women.15.25.cov.70.med)
MAE.error.infer.clust.cov.100.women.15.25.cov.70.med <- MAE(error.infer.clust.cov.100.women.15.25.cov.70.med)
ARMSE.error.infer.clust.cov.100.women.15.25.cov.70.med <- ARMSE(v1=vector.med.AD.num.women.true.cov.100.15.25, v2=vector.med.MAR.cov.70.AD.women.cl.15.25)
MRE.error.infer.clust.cov.100.women.15.25.cov.70.med <- MRE(error.infer.clust.cov.100.women.15.25.cov.70.med)
# Standard deviation
error.infer.clust.cov.100.men.15.25.cov.70.sd <- as.numeric(vector.sd.AD.num.men.true.cov.100.15.25) - as.numeric(vector.sd.MAR.cov.70.AD.men.cl.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.cov.70.sd <- RMSE(error.infer.clust.cov.100.men.15.25.cov.70.sd)
MAE.error.infer.clust.cov.100.men.15.25.cov.70.sd <- MAE(error.infer.clust.cov.100.men.15.25.cov.70.sd)
ARMSE.error.infer.clust.cov.100.men.15.25.cov.70 <- ARMSE(v1=vector.sd.AD.num.men.true.cov.100.15.25, v2=vector.sd.MAR.cov.70.AD.men.cl.15.25)
MRE.error.infer.clust.cov.100.men.15.25.cov.70.sd <- MRE(error.infer.clust.cov.100.men.15.25.cov.70.sd)
error.infer.clust.cov.100.women.15.25.cov.70.sd <- as.numeric(vector.sd.AD.num.women.true.cov.100.15.25) - as.numeric(vector.sd.MAR.cov.70.AD.women.cl.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.cov.70.sd <- RMSE(error.infer.clust.cov.100.women.15.25.cov.70.sd)
MAE.error.infer.clust.cov.100.women.15.25.cov.70.sd <- MAE(error.infer.clust.cov.100.women.15.25.cov.70.sd)
ARMSE.error.infer.clust.cov.100.women.15.25.cov.70.sd <- ARMSE(v1=vector.sd.AD.num.women.true.cov.100.15.25, v2=vector.sd.MAR.cov.70.AD.women.cl.15.25)
MRE.error.infer.clust.cov.100.women.15.25.cov.70.sd <- MRE(error.infer.clust.cov.100.women.15.25.cov.70.sd)
# 25.40
# Mean
error.infer.clust.cov.100.men.25.40.cov.70.mean <- as.numeric(vector.mean.AD.num.men.true.cov.100.25.40) - as.numeric(vector.mean.MAR.cov.70.AD.men.cl.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.cov.70.mean <- RMSE(error.infer.clust.cov.100.men.25.40.cov.70.mean)
MAE.error.infer.clust.cov.100.men.25.40.cov.70.mean <- MAE(error.infer.clust.cov.100.men.25.40.cov.70.mean)
ARMSE.error.infer.clust.cov.100.men.25.40.cov.70 <- ARMSE(v1=vector.mean.AD.num.men.true.cov.100.25.40, v2=vector.mean.MAR.cov.70.AD.men.cl.25.40)
MRE.error.infer.clust.cov.100.men.25.40.cov.70.mean <- MRE(error.infer.clust.cov.100.men.25.40.cov.70.mean)
error.infer.clust.cov.100.women.25.40.cov.70.mean <- as.numeric(vector.mean.AD.num.women.true.cov.100.25.40) - as.numeric(vector.mean.MAR.cov.70.AD.women.cl.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.cov.70.mean <- RMSE(error.infer.clust.cov.100.women.25.40.cov.70.mean)
MAE.error.infer.clust.cov.100.women.25.40.cov.70.mean <- MAE(error.infer.clust.cov.100.women.25.40.cov.70.mean)
ARMSE.error.infer.clust.cov.100.women.25.40.cov.70.mean <- ARMSE(v1=vector.mean.AD.num.women.true.cov.100.25.40, v2=vector.mean.MAR.cov.70.AD.women.cl.25.40)
MRE.error.infer.clust.cov.100.women.25.40.cov.70.mean <- MRE(error.infer.clust.cov.100.women.25.40.cov.70.mean)
# Median
error.infer.clust.cov.100.men.25.40.cov.70.med <- as.numeric(vector.med.AD.num.men.true.cov.100.25.40) - as.numeric(vector.med.MAR.cov.70.AD.men.cl.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.cov.70.med <- RMSE(error.infer.clust.cov.100.men.25.40.cov.70.med)
MAE.error.infer.clust.cov.100.men.25.40.cov.70.med <- MAE(error.infer.clust.cov.100.men.25.40.cov.70.med)
ARMSE.error.infer.clust.cov.100.men.25.40.cov.70 <- ARMSE(v1=vector.med.AD.num.men.true.cov.100.25.40, v2=vector.med.MAR.cov.70.AD.men.cl.25.40)
MRE.error.infer.clust.cov.100.men.25.40.cov.70.med <- MRE(error.infer.clust.cov.100.men.25.40.cov.70.med)
error.infer.clust.cov.100.women.25.40.cov.70.med <- as.numeric(vector.med.AD.num.women.true.cov.100.25.40) - as.numeric(vector.med.MAR.cov.70.AD.women.cl.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.cov.70.med <- RMSE(error.infer.clust.cov.100.women.25.40.cov.70.med)
MAE.error.infer.clust.cov.100.women.25.40.cov.70.med <- MAE(error.infer.clust.cov.100.women.25.40.cov.70.med)
ARMSE.error.infer.clust.cov.100.women.25.40.cov.70.med <- ARMSE(v1=vector.med.AD.num.women.true.cov.100.25.40, v2=vector.med.MAR.cov.70.AD.women.cl.25.40)
MRE.error.infer.clust.cov.100.women.25.40.cov.70.med <- MRE(error.infer.clust.cov.100.women.25.40.cov.70.med)
# Standard deviation
error.infer.clust.cov.100.men.25.40.cov.70.sd <- as.numeric(vector.sd.AD.num.men.true.cov.100.25.40) - as.numeric(vector.sd.MAR.cov.70.AD.men.cl.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.cov.70.sd <- RMSE(error.infer.clust.cov.100.men.25.40.cov.70.sd)
MAE.error.infer.clust.cov.100.men.25.40.cov.70.sd <- MAE(error.infer.clust.cov.100.men.25.40.cov.70.sd)
ARMSE.error.infer.clust.cov.100.men.25.40.cov.70 <- ARMSE(v1=vector.sd.AD.num.men.true.cov.100.25.40, v2=vector.sd.MAR.cov.70.AD.men.cl.25.40)
MRE.error.infer.clust.cov.100.men.25.40.cov.70.sd <- MRE(error.infer.clust.cov.100.men.25.40.cov.70.sd)
error.infer.clust.cov.100.women.25.40.cov.70.sd <- as.numeric(vector.sd.AD.num.women.true.cov.100.25.40) - as.numeric(vector.sd.MAR.cov.70.AD.women.cl.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.cov.70.sd <- RMSE(error.infer.clust.cov.100.women.25.40.cov.70.sd)
MAE.error.infer.clust.cov.100.women.25.40.cov.70.sd <- MAE(error.infer.clust.cov.100.women.25.40.cov.70.sd)
ARMSE.error.infer.clust.cov.100.women.25.40.cov.70.sd <- ARMSE(v1=vector.sd.AD.num.women.true.cov.100.25.40, v2=vector.sd.MAR.cov.70.AD.women.cl.25.40)
MRE.error.infer.clust.cov.100.women.25.40.cov.70.sd <- MRE(error.infer.clust.cov.100.women.25.40.cov.70.sd)
# 40.50
# Mean
error.infer.clust.cov.100.men.40.50.cov.70.mean <- as.numeric(vector.mean.AD.num.men.true.cov.100.40.50) - as.numeric(vector.mean.MAR.cov.70.AD.men.cl.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.cov.70.mean <- RMSE(error.infer.clust.cov.100.men.40.50.cov.70.mean)
MAE.error.infer.clust.cov.100.men.40.50.cov.70.mean <- MAE(error.infer.clust.cov.100.men.40.50.cov.70.mean)
ARMSE.error.infer.clust.cov.100.men.40.50.cov.70 <- ARMSE(v1=vector.mean.AD.num.men.true.cov.100.40.50, v2=vector.mean.MAR.cov.70.AD.men.cl.40.50)
MRE.error.infer.clust.cov.100.men.40.50.cov.70.mean <- MRE(error.infer.clust.cov.100.men.40.50.cov.70.mean)
error.infer.clust.cov.100.women.40.50.cov.70.mean <- as.numeric(vector.mean.AD.num.women.true.cov.100.40.50) - as.numeric(vector.mean.MAR.cov.70.AD.women.cl.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.cov.70.mean <- RMSE(error.infer.clust.cov.100.women.40.50.cov.70.mean)
MAE.error.infer.clust.cov.100.women.40.50.cov.70.mean <- MAE(error.infer.clust.cov.100.women.40.50.cov.70.mean)
ARMSE.error.infer.clust.cov.100.women.40.50.cov.70.mean <- ARMSE(v1=vector.mean.AD.num.women.true.cov.100.40.50, v2=vector.mean.MAR.cov.70.AD.women.cl.40.50)
MRE.error.infer.clust.cov.100.women.40.50.cov.70.mean <- MRE(error.infer.clust.cov.100.women.40.50.cov.70.mean)
# Median
error.infer.clust.cov.100.men.40.50.cov.70.med <- as.numeric(vector.med.AD.num.men.true.cov.100.40.50) - as.numeric(vector.med.MAR.cov.70.AD.men.cl.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.cov.70.med <- RMSE(error.infer.clust.cov.100.men.40.50.cov.70.med)
MAE.error.infer.clust.cov.100.men.40.50.cov.70.med <- MAE(error.infer.clust.cov.100.men.40.50.cov.70.med)
ARMSE.error.infer.clust.cov.100.men.40.50.cov.70 <- ARMSE(v1=vector.med.AD.num.men.true.cov.100.40.50, v2=vector.med.MAR.cov.70.AD.men.cl.40.50)
MRE.error.infer.clust.cov.100.men.40.50.cov.70.med <- MRE(error.infer.clust.cov.100.men.40.50.cov.70.med)
error.infer.clust.cov.100.women.40.50.cov.70.med <- as.numeric(vector.med.AD.num.women.true.cov.100.40.50) - as.numeric(vector.med.MAR.cov.70.AD.women.cl.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.cov.70.med <- RMSE(error.infer.clust.cov.100.women.40.50.cov.70.med)
MAE.error.infer.clust.cov.100.women.40.50.cov.70.med <- MAE(error.infer.clust.cov.100.women.40.50.cov.70.med)
ARMSE.error.infer.clust.cov.100.women.40.50.cov.70.med <- ARMSE(v1=vector.med.AD.num.women.true.cov.100.40.50, v2=vector.med.MAR.cov.70.AD.women.cl.40.50)
MRE.error.infer.clust.cov.100.women.40.50.cov.70.med <- MRE(error.infer.clust.cov.100.women.40.50.cov.70.med)
# Standard deviation
error.infer.clust.cov.100.men.40.50.cov.70.sd <- as.numeric(vector.sd.AD.num.men.true.cov.100.40.50) - as.numeric(vector.sd.MAR.cov.70.AD.men.cl.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.cov.70.sd <- RMSE(error.infer.clust.cov.100.men.40.50.cov.70.sd)
MAE.error.infer.clust.cov.100.men.40.50.cov.70.sd <- MAE(error.infer.clust.cov.100.men.40.50.cov.70.sd)
ARMSE.error.infer.clust.cov.100.men.40.50.cov.70 <- ARMSE(v1=vector.sd.AD.num.men.true.cov.100.40.50, v2=vector.sd.MAR.cov.70.AD.men.cl.40.50)
MRE.error.infer.clust.cov.100.men.40.50.cov.70.sd <- MRE(error.infer.clust.cov.100.men.40.50.cov.70.sd)
error.infer.clust.cov.100.women.40.50.cov.70.sd <- as.numeric(vector.sd.AD.num.women.true.cov.100.40.50) - as.numeric(vector.sd.MAR.cov.70.AD.women.cl.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.cov.70.sd <- RMSE(error.infer.clust.cov.100.women.40.50.cov.70.sd)
MAE.error.infer.clust.cov.100.women.40.50.cov.70.sd <- MAE(error.infer.clust.cov.100.women.40.50.cov.70.sd)
ARMSE.error.infer.clust.cov.100.women.40.50.cov.70.sd <- ARMSE(v1=vector.sd.AD.num.women.true.cov.100.40.50, v2=vector.sd.MAR.cov.70.AD.women.cl.40.50)
MRE.error.infer.clust.cov.100.women.40.50.cov.70.sd <- MRE(error.infer.clust.cov.100.women.40.50.cov.70.sd)
# Cov 75
# 15.25
# Mean
error.infer.clust.cov.100.men.15.25.cov.75.mean <- as.numeric(vector.mean.AD.num.men.true.cov.100.15.25) - as.numeric(vector.mean.MAR.cov.75.AD.men.cl.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.cov.75.mean <- RMSE(error.infer.clust.cov.100.men.15.25.cov.75.mean)
MAE.error.infer.clust.cov.100.men.15.25.cov.75.mean <- MAE(error.infer.clust.cov.100.men.15.25.cov.75.mean)
ARMSE.error.infer.clust.cov.100.men.15.25.cov.75 <- ARMSE(v1=vector.mean.AD.num.men.true.cov.100.15.25, v2=vector.mean.MAR.cov.75.AD.men.cl.15.25)
MRE.error.infer.clust.cov.100.men.15.25.cov.75.mean <- MRE(error.infer.clust.cov.100.men.15.25.cov.75.mean)
error.infer.clust.cov.100.women.15.25.cov.75.mean <- as.numeric(vector.mean.AD.num.women.true.cov.100.15.25) - as.numeric(vector.mean.MAR.cov.75.AD.women.cl.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.cov.75.mean <- RMSE(error.infer.clust.cov.100.women.15.25.cov.75.mean)
MAE.error.infer.clust.cov.100.women.15.25.cov.75.mean <- MAE(error.infer.clust.cov.100.women.15.25.cov.75.mean)
ARMSE.error.infer.clust.cov.100.women.15.25.cov.75.mean <- ARMSE(v1=vector.mean.AD.num.women.true.cov.100.15.25, v2=vector.mean.MAR.cov.75.AD.women.cl.15.25)
MRE.error.infer.clust.cov.100.women.15.25.cov.75.mean <- MRE(error.infer.clust.cov.100.women.15.25.cov.75.mean)
# Median
error.infer.clust.cov.100.men.15.25.cov.75.med <- as.numeric(vector.med.AD.num.men.true.cov.100.15.25) - as.numeric(vector.med.MAR.cov.75.AD.men.cl.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.cov.75.med <- RMSE(error.infer.clust.cov.100.men.15.25.cov.75.med)
MAE.error.infer.clust.cov.100.men.15.25.cov.75.med <- MAE(error.infer.clust.cov.100.men.15.25.cov.75.med)
ARMSE.error.infer.clust.cov.100.men.15.25.cov.75 <- ARMSE(v1=vector.med.AD.num.men.true.cov.100.15.25, v2=vector.med.MAR.cov.75.AD.men.cl.15.25)
MRE.error.infer.clust.cov.100.men.15.25.cov.75.med <- MRE(error.infer.clust.cov.100.men.15.25.cov.75.med)
error.infer.clust.cov.100.women.15.25.cov.75.med <- as.numeric(vector.med.AD.num.women.true.cov.100.15.25) - as.numeric(vector.med.MAR.cov.75.AD.women.cl.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.cov.75.med <- RMSE(error.infer.clust.cov.100.women.15.25.cov.75.med)
MAE.error.infer.clust.cov.100.women.15.25.cov.75.med <- MAE(error.infer.clust.cov.100.women.15.25.cov.75.med)
ARMSE.error.infer.clust.cov.100.women.15.25.cov.75.med <- ARMSE(v1=vector.med.AD.num.women.true.cov.100.15.25, v2=vector.med.MAR.cov.75.AD.women.cl.15.25)
MRE.error.infer.clust.cov.100.women.15.25.cov.75.med <- MRE(error.infer.clust.cov.100.women.15.25.cov.75.med)
# Standard deviation
error.infer.clust.cov.100.men.15.25.cov.75.sd <- as.numeric(vector.sd.AD.num.men.true.cov.100.15.25) - as.numeric(vector.sd.MAR.cov.75.AD.men.cl.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.cov.75.sd <- RMSE(error.infer.clust.cov.100.men.15.25.cov.75.sd)
MAE.error.infer.clust.cov.100.men.15.25.cov.75.sd <- MAE(error.infer.clust.cov.100.men.15.25.cov.75.sd)
ARMSE.error.infer.clust.cov.100.men.15.25.cov.75 <- ARMSE(v1=vector.sd.AD.num.men.true.cov.100.15.25, v2=vector.sd.MAR.cov.75.AD.men.cl.15.25)
MRE.error.infer.clust.cov.100.men.15.25.cov.75.sd <- MRE(error.infer.clust.cov.100.men.15.25.cov.75.sd)
error.infer.clust.cov.100.women.15.25.cov.75.sd <- as.numeric(vector.sd.AD.num.women.true.cov.100.15.25) - as.numeric(vector.sd.MAR.cov.75.AD.women.cl.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.cov.75.sd <- RMSE(error.infer.clust.cov.100.women.15.25.cov.75.sd)
MAE.error.infer.clust.cov.100.women.15.25.cov.75.sd <- MAE(error.infer.clust.cov.100.women.15.25.cov.75.sd)
ARMSE.error.infer.clust.cov.100.women.15.25.cov.75.sd <- ARMSE(v1=vector.sd.AD.num.women.true.cov.100.15.25, v2=vector.sd.MAR.cov.75.AD.women.cl.15.25)
MRE.error.infer.clust.cov.100.women.15.25.cov.75.sd <- MRE(error.infer.clust.cov.100.women.15.25.cov.75.sd)
# 25.40
# Mean
error.infer.clust.cov.100.men.25.40.cov.75.mean <- as.numeric(vector.mean.AD.num.men.true.cov.100.25.40) - as.numeric(vector.mean.MAR.cov.75.AD.men.cl.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.cov.75.mean <- RMSE(error.infer.clust.cov.100.men.25.40.cov.75.mean)
MAE.error.infer.clust.cov.100.men.25.40.cov.75.mean <- MAE(error.infer.clust.cov.100.men.25.40.cov.75.mean)
ARMSE.error.infer.clust.cov.100.men.25.40.cov.75 <- ARMSE(v1=vector.mean.AD.num.men.true.cov.100.25.40, v2=vector.mean.MAR.cov.75.AD.men.cl.25.40)
MRE.error.infer.clust.cov.100.men.25.40.cov.75.mean <- MRE(error.infer.clust.cov.100.men.25.40.cov.75.mean)
error.infer.clust.cov.100.women.25.40.cov.75.mean <- as.numeric(vector.mean.AD.num.women.true.cov.100.25.40) - as.numeric(vector.mean.MAR.cov.75.AD.women.cl.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.cov.75.mean <- RMSE(error.infer.clust.cov.100.women.25.40.cov.75.mean)
MAE.error.infer.clust.cov.100.women.25.40.cov.75.mean <- MAE(error.infer.clust.cov.100.women.25.40.cov.75.mean)
ARMSE.error.infer.clust.cov.100.women.25.40.cov.75.mean <- ARMSE(v1=vector.mean.AD.num.women.true.cov.100.25.40, v2=vector.mean.MAR.cov.75.AD.women.cl.25.40)
MRE.error.infer.clust.cov.100.women.25.40.cov.75.mean <- MRE(error.infer.clust.cov.100.women.25.40.cov.75.mean)
# Median
error.infer.clust.cov.100.men.25.40.cov.75.med <- as.numeric(vector.med.AD.num.men.true.cov.100.25.40) - as.numeric(vector.med.MAR.cov.75.AD.men.cl.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.cov.75.med <- RMSE(error.infer.clust.cov.100.men.25.40.cov.75.med)
MAE.error.infer.clust.cov.100.men.25.40.cov.75.med <- MAE(error.infer.clust.cov.100.men.25.40.cov.75.med)
ARMSE.error.infer.clust.cov.100.men.25.40.cov.75 <- ARMSE(v1=vector.med.AD.num.men.true.cov.100.25.40, v2=vector.med.MAR.cov.75.AD.men.cl.25.40)
MRE.error.infer.clust.cov.100.men.25.40.cov.75.med <- MRE(error.infer.clust.cov.100.men.25.40.cov.75.med)
error.infer.clust.cov.100.women.25.40.cov.75.med <- as.numeric(vector.med.AD.num.women.true.cov.100.25.40) - as.numeric(vector.med.MAR.cov.75.AD.women.cl.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.cov.75.med <- RMSE(error.infer.clust.cov.100.women.25.40.cov.75.med)
MAE.error.infer.clust.cov.100.women.25.40.cov.75.med <- MAE(error.infer.clust.cov.100.women.25.40.cov.75.med)
ARMSE.error.infer.clust.cov.100.women.25.40.cov.75.med <- ARMSE(v1=vector.med.AD.num.women.true.cov.100.25.40, v2=vector.med.MAR.cov.75.AD.women.cl.25.40)
MRE.error.infer.clust.cov.100.women.25.40.cov.75.med <- MRE(error.infer.clust.cov.100.women.25.40.cov.75.med)
# Standard deviation
error.infer.clust.cov.100.men.25.40.cov.75.sd <- as.numeric(vector.sd.AD.num.men.true.cov.100.25.40) - as.numeric(vector.sd.MAR.cov.75.AD.men.cl.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.cov.75.sd <- RMSE(error.infer.clust.cov.100.men.25.40.cov.75.sd)
MAE.error.infer.clust.cov.100.men.25.40.cov.75.sd <- MAE(error.infer.clust.cov.100.men.25.40.cov.75.sd)
ARMSE.error.infer.clust.cov.100.men.25.40.cov.75 <- ARMSE(v1=vector.sd.AD.num.men.true.cov.100.25.40, v2=vector.sd.MAR.cov.75.AD.men.cl.25.40)
MRE.error.infer.clust.cov.100.men.25.40.cov.75.sd <- MRE(error.infer.clust.cov.100.men.25.40.cov.75.sd)
error.infer.clust.cov.100.women.25.40.cov.75.sd <- as.numeric(vector.sd.AD.num.women.true.cov.100.25.40) - as.numeric(vector.sd.MAR.cov.75.AD.women.cl.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.cov.75.sd <- RMSE(error.infer.clust.cov.100.women.25.40.cov.75.sd)
MAE.error.infer.clust.cov.100.women.25.40.cov.75.sd <- MAE(error.infer.clust.cov.100.women.25.40.cov.75.sd)
ARMSE.error.infer.clust.cov.100.women.25.40.cov.75.sd <- ARMSE(v1=vector.sd.AD.num.women.true.cov.100.25.40, v2=vector.sd.MAR.cov.75.AD.women.cl.25.40)
MRE.error.infer.clust.cov.100.women.25.40.cov.75.sd <- MRE(error.infer.clust.cov.100.women.25.40.cov.75.sd)
# 40.50
# Mean
error.infer.clust.cov.100.men.40.50.cov.75.mean <- as.numeric(vector.mean.AD.num.men.true.cov.100.40.50) - as.numeric(vector.mean.MAR.cov.75.AD.men.cl.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.cov.75.mean <- RMSE(error.infer.clust.cov.100.men.40.50.cov.75.mean)
MAE.error.infer.clust.cov.100.men.40.50.cov.75.mean <- MAE(error.infer.clust.cov.100.men.40.50.cov.75.mean)
ARMSE.error.infer.clust.cov.100.men.40.50.cov.75 <- ARMSE(v1=vector.mean.AD.num.men.true.cov.100.40.50, v2=vector.mean.MAR.cov.75.AD.men.cl.40.50)
MRE.error.infer.clust.cov.100.men.40.50.cov.75.mean <- MRE(error.infer.clust.cov.100.men.40.50.cov.75.mean)
error.infer.clust.cov.100.women.40.50.cov.75.mean <- as.numeric(vector.mean.AD.num.women.true.cov.100.40.50) - as.numeric(vector.mean.MAR.cov.75.AD.women.cl.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.cov.75.mean <- RMSE(error.infer.clust.cov.100.women.40.50.cov.75.mean)
MAE.error.infer.clust.cov.100.women.40.50.cov.75.mean <- MAE(error.infer.clust.cov.100.women.40.50.cov.75.mean)
ARMSE.error.infer.clust.cov.100.women.40.50.cov.75.mean <- ARMSE(v1=vector.mean.AD.num.women.true.cov.100.40.50, v2=vector.mean.MAR.cov.75.AD.women.cl.40.50)
MRE.error.infer.clust.cov.100.women.40.50.cov.75.mean <- MRE(error.infer.clust.cov.100.women.40.50.cov.75.mean)
# Median
error.infer.clust.cov.100.men.40.50.cov.75.med <- as.numeric(vector.med.AD.num.men.true.cov.100.40.50) - as.numeric(vector.med.MAR.cov.75.AD.men.cl.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.cov.75.med <- RMSE(error.infer.clust.cov.100.men.40.50.cov.75.med)
MAE.error.infer.clust.cov.100.men.40.50.cov.75.med <- MAE(error.infer.clust.cov.100.men.40.50.cov.75.med)
ARMSE.error.infer.clust.cov.100.men.40.50.cov.75 <- ARMSE(v1=vector.med.AD.num.men.true.cov.100.40.50, v2=vector.med.MAR.cov.75.AD.men.cl.40.50)
MRE.error.infer.clust.cov.100.men.40.50.cov.75.med <- MRE(error.infer.clust.cov.100.men.40.50.cov.75.med)
error.infer.clust.cov.100.women.40.50.cov.75.med <- as.numeric(vector.med.AD.num.women.true.cov.100.40.50) - as.numeric(vector.med.MAR.cov.75.AD.women.cl.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.cov.75.med <- RMSE(error.infer.clust.cov.100.women.40.50.cov.75.med)
MAE.error.infer.clust.cov.100.women.40.50.cov.75.med <- MAE(error.infer.clust.cov.100.women.40.50.cov.75.med)
ARMSE.error.infer.clust.cov.100.women.40.50.cov.75.med <- ARMSE(v1=vector.med.AD.num.women.true.cov.100.40.50, v2=vector.med.MAR.cov.75.AD.women.cl.40.50)
MRE.error.infer.clust.cov.100.women.40.50.cov.75.med <- MRE(error.infer.clust.cov.100.women.40.50.cov.75.med)
# Standard deviation
error.infer.clust.cov.100.men.40.50.cov.75.sd <- as.numeric(vector.sd.AD.num.men.true.cov.100.40.50) - as.numeric(vector.sd.MAR.cov.75.AD.men.cl.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.cov.75.sd <- RMSE(error.infer.clust.cov.100.men.40.50.cov.75.sd)
MAE.error.infer.clust.cov.100.men.40.50.cov.75.sd <- MAE(error.infer.clust.cov.100.men.40.50.cov.75.sd)
ARMSE.error.infer.clust.cov.100.men.40.50.cov.75 <- ARMSE(v1=vector.sd.AD.num.men.true.cov.100.40.50, v2=vector.sd.MAR.cov.75.AD.men.cl.40.50)
MRE.error.infer.clust.cov.100.men.40.50.cov.75.sd <- MRE(error.infer.clust.cov.100.men.40.50.cov.75.sd)
error.infer.clust.cov.100.women.40.50.cov.75.sd <- as.numeric(vector.sd.AD.num.women.true.cov.100.40.50) - as.numeric(vector.sd.MAR.cov.75.AD.women.cl.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.cov.75.sd <- RMSE(error.infer.clust.cov.100.women.40.50.cov.75.sd)
MAE.error.infer.clust.cov.100.women.40.50.cov.75.sd <- MAE(error.infer.clust.cov.100.women.40.50.cov.75.sd)
ARMSE.error.infer.clust.cov.100.women.40.50.cov.75.sd <- ARMSE(v1=vector.sd.AD.num.women.true.cov.100.40.50, v2=vector.sd.MAR.cov.75.AD.women.cl.40.50)
MRE.error.infer.clust.cov.100.women.40.50.cov.75.sd <- MRE(error.infer.clust.cov.100.women.40.50.cov.75.sd)
# Cov 80
# 15.25
# Mean
error.infer.clust.cov.100.men.15.25.cov.80.mean <- as.numeric(vector.mean.AD.num.men.true.cov.100.15.25) - as.numeric(vector.mean.MAR.cov.80.AD.men.cl.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.cov.80.mean <- RMSE(error.infer.clust.cov.100.men.15.25.cov.80.mean)
MAE.error.infer.clust.cov.100.men.15.25.cov.80.mean <- MAE(error.infer.clust.cov.100.men.15.25.cov.80.mean)
ARMSE.error.infer.clust.cov.100.men.15.25.cov.80 <- ARMSE(v1=vector.mean.AD.num.men.true.cov.100.15.25, v2=vector.mean.MAR.cov.80.AD.men.cl.15.25)
MRE.error.infer.clust.cov.100.men.15.25.cov.80.mean <- MRE(error.infer.clust.cov.100.men.15.25.cov.80.mean)
error.infer.clust.cov.100.women.15.25.cov.80.mean <- as.numeric(vector.mean.AD.num.women.true.cov.100.15.25) - as.numeric(vector.mean.MAR.cov.80.AD.women.cl.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.cov.80.mean <- RMSE(error.infer.clust.cov.100.women.15.25.cov.80.mean)
MAE.error.infer.clust.cov.100.women.15.25.cov.80.mean <- MAE(error.infer.clust.cov.100.women.15.25.cov.80.mean)
ARMSE.error.infer.clust.cov.100.women.15.25.cov.80.mean <- ARMSE(v1=vector.mean.AD.num.women.true.cov.100.15.25, v2=vector.mean.MAR.cov.80.AD.women.cl.15.25)
MRE.error.infer.clust.cov.100.women.15.25.cov.80.mean <- MRE(error.infer.clust.cov.100.women.15.25.cov.80.mean)
# Median
error.infer.clust.cov.100.men.15.25.cov.80.med <- as.numeric(vector.med.AD.num.men.true.cov.100.15.25) - as.numeric(vector.med.MAR.cov.80.AD.men.cl.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.cov.80.med <- RMSE(error.infer.clust.cov.100.men.15.25.cov.80.med)
MAE.error.infer.clust.cov.100.men.15.25.cov.80.med <- MAE(error.infer.clust.cov.100.men.15.25.cov.80.med)
ARMSE.error.infer.clust.cov.100.men.15.25.cov.80 <- ARMSE(v1=vector.med.AD.num.men.true.cov.100.15.25, v2=vector.med.MAR.cov.80.AD.men.cl.15.25)
MRE.error.infer.clust.cov.100.men.15.25.cov.80.med <- MRE(error.infer.clust.cov.100.men.15.25.cov.80.med)
error.infer.clust.cov.100.women.15.25.cov.80.med <- as.numeric(vector.med.AD.num.women.true.cov.100.15.25) - as.numeric(vector.med.MAR.cov.80.AD.women.cl.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.cov.80.med <- RMSE(error.infer.clust.cov.100.women.15.25.cov.80.med)
MAE.error.infer.clust.cov.100.women.15.25.cov.80.med <- MAE(error.infer.clust.cov.100.women.15.25.cov.80.med)
ARMSE.error.infer.clust.cov.100.women.15.25.cov.80.med <- ARMSE(v1=vector.med.AD.num.women.true.cov.100.15.25, v2=vector.med.MAR.cov.80.AD.women.cl.15.25)
MRE.error.infer.clust.cov.100.women.15.25.cov.80.med <- MRE(error.infer.clust.cov.100.women.15.25.cov.80.med)
# Standard deviation
error.infer.clust.cov.100.men.15.25.cov.80.sd <- as.numeric(vector.sd.AD.num.men.true.cov.100.15.25) - as.numeric(vector.sd.MAR.cov.80.AD.men.cl.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.cov.80.sd <- RMSE(error.infer.clust.cov.100.men.15.25.cov.80.sd)
MAE.error.infer.clust.cov.100.men.15.25.cov.80.sd <- MAE(error.infer.clust.cov.100.men.15.25.cov.80.sd)
ARMSE.error.infer.clust.cov.100.men.15.25.cov.80 <- ARMSE(v1=vector.sd.AD.num.men.true.cov.100.15.25, v2=vector.sd.MAR.cov.80.AD.men.cl.15.25)
MRE.error.infer.clust.cov.100.men.15.25.cov.80.sd <- MRE(error.infer.clust.cov.100.men.15.25.cov.80.sd)
error.infer.clust.cov.100.women.15.25.cov.80.sd <- as.numeric(vector.sd.AD.num.women.true.cov.100.15.25) - as.numeric(vector.sd.MAR.cov.80.AD.women.cl.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.cov.80.sd <- RMSE(error.infer.clust.cov.100.women.15.25.cov.80.sd)
MAE.error.infer.clust.cov.100.women.15.25.cov.80.sd <- MAE(error.infer.clust.cov.100.women.15.25.cov.80.sd)
ARMSE.error.infer.clust.cov.100.women.15.25.cov.80.sd <- ARMSE(v1=vector.sd.AD.num.women.true.cov.100.15.25, v2=vector.sd.MAR.cov.80.AD.women.cl.15.25)
MRE.error.infer.clust.cov.100.women.15.25.cov.80.sd <- MRE(error.infer.clust.cov.100.women.15.25.cov.80.sd)
# 25.40
# Mean
error.infer.clust.cov.100.men.25.40.cov.80.mean <- as.numeric(vector.mean.AD.num.men.true.cov.100.25.40) - as.numeric(vector.mean.MAR.cov.80.AD.men.cl.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.cov.80.mean <- RMSE(error.infer.clust.cov.100.men.25.40.cov.80.mean)
MAE.error.infer.clust.cov.100.men.25.40.cov.80.mean <- MAE(error.infer.clust.cov.100.men.25.40.cov.80.mean)
ARMSE.error.infer.clust.cov.100.men.25.40.cov.80 <- ARMSE(v1=vector.mean.AD.num.men.true.cov.100.25.40, v2=vector.mean.MAR.cov.80.AD.men.cl.25.40)
MRE.error.infer.clust.cov.100.men.25.40.cov.80.mean <- MRE(error.infer.clust.cov.100.men.25.40.cov.80.mean)
error.infer.clust.cov.100.women.25.40.cov.80.mean <- as.numeric(vector.mean.AD.num.women.true.cov.100.25.40) - as.numeric(vector.mean.MAR.cov.80.AD.women.cl.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.cov.80.mean <- RMSE(error.infer.clust.cov.100.women.25.40.cov.80.mean)
MAE.error.infer.clust.cov.100.women.25.40.cov.80.mean <- MAE(error.infer.clust.cov.100.women.25.40.cov.80.mean)
ARMSE.error.infer.clust.cov.100.women.25.40.cov.80.mean <- ARMSE(v1=vector.mean.AD.num.women.true.cov.100.25.40, v2=vector.mean.MAR.cov.80.AD.women.cl.25.40)
MRE.error.infer.clust.cov.100.women.25.40.cov.80.mean <- MRE(error.infer.clust.cov.100.women.25.40.cov.80.mean)
# Median
error.infer.clust.cov.100.men.25.40.cov.80.med <- as.numeric(vector.med.AD.num.men.true.cov.100.25.40) - as.numeric(vector.med.MAR.cov.80.AD.men.cl.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.cov.80.med <- RMSE(error.infer.clust.cov.100.men.25.40.cov.80.med)
MAE.error.infer.clust.cov.100.men.25.40.cov.80.med <- MAE(error.infer.clust.cov.100.men.25.40.cov.80.med)
ARMSE.error.infer.clust.cov.100.men.25.40.cov.80 <- ARMSE(v1=vector.med.AD.num.men.true.cov.100.25.40, v2=vector.med.MAR.cov.80.AD.men.cl.25.40)
MRE.error.infer.clust.cov.100.men.25.40.cov.80.med <- MRE(error.infer.clust.cov.100.men.25.40.cov.80.med)
error.infer.clust.cov.100.women.25.40.cov.80.med <- as.numeric(vector.med.AD.num.women.true.cov.100.25.40) - as.numeric(vector.med.MAR.cov.80.AD.women.cl.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.cov.80.med <- RMSE(error.infer.clust.cov.100.women.25.40.cov.80.med)
MAE.error.infer.clust.cov.100.women.25.40.cov.80.med <- MAE(error.infer.clust.cov.100.women.25.40.cov.80.med)
ARMSE.error.infer.clust.cov.100.women.25.40.cov.80.med <- ARMSE(v1=vector.med.AD.num.women.true.cov.100.25.40, v2=vector.med.MAR.cov.80.AD.women.cl.25.40)
MRE.error.infer.clust.cov.100.women.25.40.cov.80.med <- MRE(error.infer.clust.cov.100.women.25.40.cov.80.med)
# Standard deviation
error.infer.clust.cov.100.men.25.40.cov.80.sd <- as.numeric(vector.sd.AD.num.men.true.cov.100.25.40) - as.numeric(vector.sd.MAR.cov.80.AD.men.cl.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.cov.80.sd <- RMSE(error.infer.clust.cov.100.men.25.40.cov.80.sd)
MAE.error.infer.clust.cov.100.men.25.40.cov.80.sd <- MAE(error.infer.clust.cov.100.men.25.40.cov.80.sd)
ARMSE.error.infer.clust.cov.100.men.25.40.cov.80 <- ARMSE(v1=vector.sd.AD.num.men.true.cov.100.25.40, v2=vector.sd.MAR.cov.80.AD.men.cl.25.40)
MRE.error.infer.clust.cov.100.men.25.40.cov.80.sd <- MRE(error.infer.clust.cov.100.men.25.40.cov.80.sd)
error.infer.clust.cov.100.women.25.40.cov.80.sd <- as.numeric(vector.sd.AD.num.women.true.cov.100.25.40) - as.numeric(vector.sd.MAR.cov.80.AD.women.cl.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.cov.80.sd <- RMSE(error.infer.clust.cov.100.women.25.40.cov.80.sd)
MAE.error.infer.clust.cov.100.women.25.40.cov.80.sd <- MAE(error.infer.clust.cov.100.women.25.40.cov.80.sd)
ARMSE.error.infer.clust.cov.100.women.25.40.cov.80.sd <- ARMSE(v1=vector.sd.AD.num.women.true.cov.100.25.40, v2=vector.sd.MAR.cov.80.AD.women.cl.25.40)
MRE.error.infer.clust.cov.100.women.25.40.cov.80.sd <- MRE(error.infer.clust.cov.100.women.25.40.cov.80.sd)
# 40.50
# Mean
error.infer.clust.cov.100.men.40.50.cov.80.mean <- as.numeric(vector.mean.AD.num.men.true.cov.100.40.50) - as.numeric(vector.mean.MAR.cov.80.AD.men.cl.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.cov.80.mean <- RMSE(error.infer.clust.cov.100.men.40.50.cov.80.mean)
MAE.error.infer.clust.cov.100.men.40.50.cov.80.mean <- MAE(error.infer.clust.cov.100.men.40.50.cov.80.mean)
ARMSE.error.infer.clust.cov.100.men.40.50.cov.80 <- ARMSE(v1=vector.mean.AD.num.men.true.cov.100.40.50, v2=vector.mean.MAR.cov.80.AD.men.cl.40.50)
MRE.error.infer.clust.cov.100.men.40.50.cov.80.mean <- MRE(error.infer.clust.cov.100.men.40.50.cov.80.mean)
error.infer.clust.cov.100.women.40.50.cov.80.mean <- as.numeric(vector.mean.AD.num.women.true.cov.100.40.50) - as.numeric(vector.mean.MAR.cov.80.AD.women.cl.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.cov.80.mean <- RMSE(error.infer.clust.cov.100.women.40.50.cov.80.mean)
MAE.error.infer.clust.cov.100.women.40.50.cov.80.mean <- MAE(error.infer.clust.cov.100.women.40.50.cov.80.mean)
ARMSE.error.infer.clust.cov.100.women.40.50.cov.80.mean <- ARMSE(v1=vector.mean.AD.num.women.true.cov.100.40.50, v2=vector.mean.MAR.cov.80.AD.women.cl.40.50)
MRE.error.infer.clust.cov.100.women.40.50.cov.80.mean <- MRE(error.infer.clust.cov.100.women.40.50.cov.80.mean)
# Median
error.infer.clust.cov.100.men.40.50.cov.80.med <- as.numeric(vector.med.AD.num.men.true.cov.100.40.50) - as.numeric(vector.med.MAR.cov.80.AD.men.cl.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.cov.80.med <- RMSE(error.infer.clust.cov.100.men.40.50.cov.80.med)
MAE.error.infer.clust.cov.100.men.40.50.cov.80.med <- MAE(error.infer.clust.cov.100.men.40.50.cov.80.med)
ARMSE.error.infer.clust.cov.100.men.40.50.cov.80 <- ARMSE(v1=vector.med.AD.num.men.true.cov.100.40.50, v2=vector.med.MAR.cov.80.AD.men.cl.40.50)
MRE.error.infer.clust.cov.100.men.40.50.cov.80.med <- MRE(error.infer.clust.cov.100.men.40.50.cov.80.med)
error.infer.clust.cov.100.women.40.50.cov.80.med <- as.numeric(vector.med.AD.num.women.true.cov.100.40.50) - as.numeric(vector.med.MAR.cov.80.AD.women.cl.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.cov.80.med <- RMSE(error.infer.clust.cov.100.women.40.50.cov.80.med)
MAE.error.infer.clust.cov.100.women.40.50.cov.80.med <- MAE(error.infer.clust.cov.100.women.40.50.cov.80.med)
ARMSE.error.infer.clust.cov.100.women.40.50.cov.80.med <- ARMSE(v1=vector.med.AD.num.women.true.cov.100.40.50, v2=vector.med.MAR.cov.80.AD.women.cl.40.50)
MRE.error.infer.clust.cov.100.women.40.50.cov.80.med <- MRE(error.infer.clust.cov.100.women.40.50.cov.80.med)
# Standard deviation
error.infer.clust.cov.100.men.40.50.cov.80.sd <- as.numeric(vector.sd.AD.num.men.true.cov.100.40.50) - as.numeric(vector.sd.MAR.cov.80.AD.men.cl.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.cov.80.sd <- RMSE(error.infer.clust.cov.100.men.40.50.cov.80.sd)
MAE.error.infer.clust.cov.100.men.40.50.cov.80.sd <- MAE(error.infer.clust.cov.100.men.40.50.cov.80.sd)
ARMSE.error.infer.clust.cov.100.men.40.50.cov.80 <- ARMSE(v1=vector.sd.AD.num.men.true.cov.100.40.50, v2=vector.sd.MAR.cov.80.AD.men.cl.40.50)
MRE.error.infer.clust.cov.100.men.40.50.cov.80.sd <- MRE(error.infer.clust.cov.100.men.40.50.cov.80.sd)
error.infer.clust.cov.100.women.40.50.cov.80.sd <- as.numeric(vector.sd.AD.num.women.true.cov.100.40.50) - as.numeric(vector.sd.MAR.cov.80.AD.women.cl.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.cov.80.sd <- RMSE(error.infer.clust.cov.100.women.40.50.cov.80.sd)
MAE.error.infer.clust.cov.100.women.40.50.cov.80.sd <- MAE(error.infer.clust.cov.100.women.40.50.cov.80.sd)
ARMSE.error.infer.clust.cov.100.women.40.50.cov.80.sd <- ARMSE(v1=vector.sd.AD.num.women.true.cov.100.40.50, v2=vector.sd.MAR.cov.80.AD.women.cl.40.50)
MRE.error.infer.clust.cov.100.women.40.50.cov.80.sd <- MRE(error.infer.clust.cov.100.women.40.50.cov.80.sd)
# Cov 85
# 15.25
# Mean
error.infer.clust.cov.100.men.15.25.cov.85.mean <- as.numeric(vector.mean.AD.num.men.true.cov.100.15.25) - as.numeric(vector.mean.MAR.cov.85.AD.men.cl.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.cov.85.mean <- RMSE(error.infer.clust.cov.100.men.15.25.cov.85.mean)
MAE.error.infer.clust.cov.100.men.15.25.cov.85.mean <- MAE(error.infer.clust.cov.100.men.15.25.cov.85.mean)
ARMSE.error.infer.clust.cov.100.men.15.25.cov.85 <- ARMSE(v1=vector.mean.AD.num.men.true.cov.100.15.25, v2=vector.mean.MAR.cov.85.AD.men.cl.15.25)
MRE.error.infer.clust.cov.100.men.15.25.cov.85.mean <- MRE(error.infer.clust.cov.100.men.15.25.cov.85.mean)
error.infer.clust.cov.100.women.15.25.cov.85.mean <- as.numeric(vector.mean.AD.num.women.true.cov.100.15.25) - as.numeric(vector.mean.MAR.cov.85.AD.women.cl.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.cov.85.mean <- RMSE(error.infer.clust.cov.100.women.15.25.cov.85.mean)
MAE.error.infer.clust.cov.100.women.15.25.cov.85.mean <- MAE(error.infer.clust.cov.100.women.15.25.cov.85.mean)
ARMSE.error.infer.clust.cov.100.women.15.25.cov.85.mean <- ARMSE(v1=vector.mean.AD.num.women.true.cov.100.15.25, v2=vector.mean.MAR.cov.85.AD.women.cl.15.25)
MRE.error.infer.clust.cov.100.women.15.25.cov.85.mean <- MRE(error.infer.clust.cov.100.women.15.25.cov.85.mean)
# Median
error.infer.clust.cov.100.men.15.25.cov.85.med <- as.numeric(vector.med.AD.num.men.true.cov.100.15.25) - as.numeric(vector.med.MAR.cov.85.AD.men.cl.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.cov.85.med <- RMSE(error.infer.clust.cov.100.men.15.25.cov.85.med)
MAE.error.infer.clust.cov.100.men.15.25.cov.85.med <- MAE(error.infer.clust.cov.100.men.15.25.cov.85.med)
ARMSE.error.infer.clust.cov.100.men.15.25.cov.85 <- ARMSE(v1=vector.med.AD.num.men.true.cov.100.15.25, v2=vector.med.MAR.cov.85.AD.men.cl.15.25)
MRE.error.infer.clust.cov.100.men.15.25.cov.85.med <- MRE(error.infer.clust.cov.100.men.15.25.cov.85.med)
error.infer.clust.cov.100.women.15.25.cov.85.med <- as.numeric(vector.med.AD.num.women.true.cov.100.15.25) - as.numeric(vector.med.MAR.cov.85.AD.women.cl.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.cov.85.med <- RMSE(error.infer.clust.cov.100.women.15.25.cov.85.med)
MAE.error.infer.clust.cov.100.women.15.25.cov.85.med <- MAE(error.infer.clust.cov.100.women.15.25.cov.85.med)
ARMSE.error.infer.clust.cov.100.women.15.25.cov.85.med <- ARMSE(v1=vector.med.AD.num.women.true.cov.100.15.25, v2=vector.med.MAR.cov.85.AD.women.cl.15.25)
MRE.error.infer.clust.cov.100.women.15.25.cov.85.med <- MRE(error.infer.clust.cov.100.women.15.25.cov.85.med)
# Standard deviation
error.infer.clust.cov.100.men.15.25.cov.85.sd <- as.numeric(vector.sd.AD.num.men.true.cov.100.15.25) - as.numeric(vector.sd.MAR.cov.85.AD.men.cl.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.cov.85.sd <- RMSE(error.infer.clust.cov.100.men.15.25.cov.85.sd)
MAE.error.infer.clust.cov.100.men.15.25.cov.85.sd <- MAE(error.infer.clust.cov.100.men.15.25.cov.85.sd)
ARMSE.error.infer.clust.cov.100.men.15.25.cov.85 <- ARMSE(v1=vector.sd.AD.num.men.true.cov.100.15.25, v2=vector.sd.MAR.cov.85.AD.men.cl.15.25)
MRE.error.infer.clust.cov.100.men.15.25.cov.85.sd <- MRE(error.infer.clust.cov.100.men.15.25.cov.85.sd)
error.infer.clust.cov.100.women.15.25.cov.85.sd <- as.numeric(vector.sd.AD.num.women.true.cov.100.15.25) - as.numeric(vector.sd.MAR.cov.85.AD.women.cl.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.cov.85.sd <- RMSE(error.infer.clust.cov.100.women.15.25.cov.85.sd)
MAE.error.infer.clust.cov.100.women.15.25.cov.85.sd <- MAE(error.infer.clust.cov.100.women.15.25.cov.85.sd)
ARMSE.error.infer.clust.cov.100.women.15.25.cov.85.sd <- ARMSE(v1=vector.sd.AD.num.women.true.cov.100.15.25, v2=vector.sd.MAR.cov.85.AD.women.cl.15.25)
MRE.error.infer.clust.cov.100.women.15.25.cov.85.sd <- MRE(error.infer.clust.cov.100.women.15.25.cov.85.sd)
# 25.40
# Mean
error.infer.clust.cov.100.men.25.40.cov.85.mean <- as.numeric(vector.mean.AD.num.men.true.cov.100.25.40) - as.numeric(vector.mean.MAR.cov.85.AD.men.cl.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.cov.85.mean <- RMSE(error.infer.clust.cov.100.men.25.40.cov.85.mean)
MAE.error.infer.clust.cov.100.men.25.40.cov.85.mean <- MAE(error.infer.clust.cov.100.men.25.40.cov.85.mean)
ARMSE.error.infer.clust.cov.100.men.25.40.cov.85 <- ARMSE(v1=vector.mean.AD.num.men.true.cov.100.25.40, v2=vector.mean.MAR.cov.85.AD.men.cl.25.40)
MRE.error.infer.clust.cov.100.men.25.40.cov.85.mean <- MRE(error.infer.clust.cov.100.men.25.40.cov.85.mean)
error.infer.clust.cov.100.women.25.40.cov.85.mean <- as.numeric(vector.mean.AD.num.women.true.cov.100.25.40) - as.numeric(vector.mean.MAR.cov.85.AD.women.cl.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.cov.85.mean <- RMSE(error.infer.clust.cov.100.women.25.40.cov.85.mean)
MAE.error.infer.clust.cov.100.women.25.40.cov.85.mean <- MAE(error.infer.clust.cov.100.women.25.40.cov.85.mean)
ARMSE.error.infer.clust.cov.100.women.25.40.cov.85.mean <- ARMSE(v1=vector.mean.AD.num.women.true.cov.100.25.40, v2=vector.mean.MAR.cov.85.AD.women.cl.25.40)
MRE.error.infer.clust.cov.100.women.25.40.cov.85.mean <- MRE(error.infer.clust.cov.100.women.25.40.cov.85.mean)
# Median
error.infer.clust.cov.100.men.25.40.cov.85.med <- as.numeric(vector.med.AD.num.men.true.cov.100.25.40) - as.numeric(vector.med.MAR.cov.85.AD.men.cl.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.cov.85.med <- RMSE(error.infer.clust.cov.100.men.25.40.cov.85.med)
MAE.error.infer.clust.cov.100.men.25.40.cov.85.med <- MAE(error.infer.clust.cov.100.men.25.40.cov.85.med)
ARMSE.error.infer.clust.cov.100.men.25.40.cov.85 <- ARMSE(v1=vector.med.AD.num.men.true.cov.100.25.40, v2=vector.med.MAR.cov.85.AD.men.cl.25.40)
MRE.error.infer.clust.cov.100.men.25.40.cov.85.med <- MRE(error.infer.clust.cov.100.men.25.40.cov.85.med)
error.infer.clust.cov.100.women.25.40.cov.85.med <- as.numeric(vector.med.AD.num.women.true.cov.100.25.40) - as.numeric(vector.med.MAR.cov.85.AD.women.cl.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.cov.85.med <- RMSE(error.infer.clust.cov.100.women.25.40.cov.85.med)
MAE.error.infer.clust.cov.100.women.25.40.cov.85.med <- MAE(error.infer.clust.cov.100.women.25.40.cov.85.med)
ARMSE.error.infer.clust.cov.100.women.25.40.cov.85.med <- ARMSE(v1=vector.med.AD.num.women.true.cov.100.25.40, v2=vector.med.MAR.cov.85.AD.women.cl.25.40)
MRE.error.infer.clust.cov.100.women.25.40.cov.85.med <- MRE(error.infer.clust.cov.100.women.25.40.cov.85.med)
# Standard deviation
error.infer.clust.cov.100.men.25.40.cov.85.sd <- as.numeric(vector.sd.AD.num.men.true.cov.100.25.40) - as.numeric(vector.sd.MAR.cov.85.AD.men.cl.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.cov.85.sd <- RMSE(error.infer.clust.cov.100.men.25.40.cov.85.sd)
MAE.error.infer.clust.cov.100.men.25.40.cov.85.sd <- MAE(error.infer.clust.cov.100.men.25.40.cov.85.sd)
ARMSE.error.infer.clust.cov.100.men.25.40.cov.85 <- ARMSE(v1=vector.sd.AD.num.men.true.cov.100.25.40, v2=vector.sd.MAR.cov.85.AD.men.cl.25.40)
MRE.error.infer.clust.cov.100.men.25.40.cov.85.sd <- MRE(error.infer.clust.cov.100.men.25.40.cov.85.sd)
error.infer.clust.cov.100.women.25.40.cov.85.sd <- as.numeric(vector.sd.AD.num.women.true.cov.100.25.40) - as.numeric(vector.sd.MAR.cov.85.AD.women.cl.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.cov.85.sd <- RMSE(error.infer.clust.cov.100.women.25.40.cov.85.sd)
MAE.error.infer.clust.cov.100.women.25.40.cov.85.sd <- MAE(error.infer.clust.cov.100.women.25.40.cov.85.sd)
ARMSE.error.infer.clust.cov.100.women.25.40.cov.85.sd <- ARMSE(v1=vector.sd.AD.num.women.true.cov.100.25.40, v2=vector.sd.MAR.cov.85.AD.women.cl.25.40)
MRE.error.infer.clust.cov.100.women.25.40.cov.85.sd <- MRE(error.infer.clust.cov.100.women.25.40.cov.85.sd)
# 40.50
# Mean
error.infer.clust.cov.100.men.40.50.cov.85.mean <- as.numeric(vector.mean.AD.num.men.true.cov.100.40.50) - as.numeric(vector.mean.MAR.cov.85.AD.men.cl.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.cov.85.mean <- RMSE(error.infer.clust.cov.100.men.40.50.cov.85.mean)
MAE.error.infer.clust.cov.100.men.40.50.cov.85.mean <- MAE(error.infer.clust.cov.100.men.40.50.cov.85.mean)
ARMSE.error.infer.clust.cov.100.men.40.50.cov.85 <- ARMSE(v1=vector.mean.AD.num.men.true.cov.100.40.50, v2=vector.mean.MAR.cov.85.AD.men.cl.40.50)
MRE.error.infer.clust.cov.100.men.40.50.cov.85.mean <- MRE(error.infer.clust.cov.100.men.40.50.cov.85.mean)
error.infer.clust.cov.100.women.40.50.cov.85.mean <- as.numeric(vector.mean.AD.num.women.true.cov.100.40.50) - as.numeric(vector.mean.MAR.cov.85.AD.women.cl.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.cov.85.mean <- RMSE(error.infer.clust.cov.100.women.40.50.cov.85.mean)
MAE.error.infer.clust.cov.100.women.40.50.cov.85.mean <- MAE(error.infer.clust.cov.100.women.40.50.cov.85.mean)
ARMSE.error.infer.clust.cov.100.women.40.50.cov.85.mean <- ARMSE(v1=vector.mean.AD.num.women.true.cov.100.40.50, v2=vector.mean.MAR.cov.85.AD.women.cl.40.50)
MRE.error.infer.clust.cov.100.women.40.50.cov.85.mean <- MRE(error.infer.clust.cov.100.women.40.50.cov.85.mean)
# Median
error.infer.clust.cov.100.men.40.50.cov.85.med <- as.numeric(vector.med.AD.num.men.true.cov.100.40.50) - as.numeric(vector.med.MAR.cov.85.AD.men.cl.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.cov.85.med <- RMSE(error.infer.clust.cov.100.men.40.50.cov.85.med)
MAE.error.infer.clust.cov.100.men.40.50.cov.85.med <- MAE(error.infer.clust.cov.100.men.40.50.cov.85.med)
ARMSE.error.infer.clust.cov.100.men.40.50.cov.85 <- ARMSE(v1=vector.med.AD.num.men.true.cov.100.40.50, v2=vector.med.MAR.cov.85.AD.men.cl.40.50)
MRE.error.infer.clust.cov.100.men.40.50.cov.85.med <- MRE(error.infer.clust.cov.100.men.40.50.cov.85.med)
error.infer.clust.cov.100.women.40.50.cov.85.med <- as.numeric(vector.med.AD.num.women.true.cov.100.40.50) - as.numeric(vector.med.MAR.cov.85.AD.women.cl.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.cov.85.med <- RMSE(error.infer.clust.cov.100.women.40.50.cov.85.med)
MAE.error.infer.clust.cov.100.women.40.50.cov.85.med <- MAE(error.infer.clust.cov.100.women.40.50.cov.85.med)
ARMSE.error.infer.clust.cov.100.women.40.50.cov.85.med <- ARMSE(v1=vector.med.AD.num.women.true.cov.100.40.50, v2=vector.med.MAR.cov.85.AD.women.cl.40.50)
MRE.error.infer.clust.cov.100.women.40.50.cov.85.med <- MRE(error.infer.clust.cov.100.women.40.50.cov.85.med)
# Standard deviation
error.infer.clust.cov.100.men.40.50.cov.85.sd <- as.numeric(vector.sd.AD.num.men.true.cov.100.40.50) - as.numeric(vector.sd.MAR.cov.85.AD.men.cl.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.cov.85.sd <- RMSE(error.infer.clust.cov.100.men.40.50.cov.85.sd)
MAE.error.infer.clust.cov.100.men.40.50.cov.85.sd <- MAE(error.infer.clust.cov.100.men.40.50.cov.85.sd)
ARMSE.error.infer.clust.cov.100.men.40.50.cov.85 <- ARMSE(v1=vector.sd.AD.num.men.true.cov.100.40.50, v2=vector.sd.MAR.cov.85.AD.men.cl.40.50)
MRE.error.infer.clust.cov.100.men.40.50.cov.85.sd <- MRE(error.infer.clust.cov.100.men.40.50.cov.85.sd)
error.infer.clust.cov.100.women.40.50.cov.85.sd <- as.numeric(vector.sd.AD.num.women.true.cov.100.40.50) - as.numeric(vector.sd.MAR.cov.85.AD.women.cl.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.cov.85.sd <- RMSE(error.infer.clust.cov.100.women.40.50.cov.85.sd)
MAE.error.infer.clust.cov.100.women.40.50.cov.85.sd <- MAE(error.infer.clust.cov.100.women.40.50.cov.85.sd)
ARMSE.error.infer.clust.cov.100.women.40.50.cov.85.sd <- ARMSE(v1=vector.sd.AD.num.women.true.cov.100.40.50, v2=vector.sd.MAR.cov.85.AD.women.cl.40.50)
MRE.error.infer.clust.cov.100.women.40.50.cov.85.sd <- MRE(error.infer.clust.cov.100.women.40.50.cov.85.sd)
# Cov 90
# 15.25
# Mean
error.infer.clust.cov.100.men.15.25.cov.90.mean <- as.numeric(vector.mean.AD.num.men.true.cov.100.15.25) - as.numeric(vector.mean.MAR.cov.90.AD.men.cl.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.cov.90.mean <- RMSE(error.infer.clust.cov.100.men.15.25.cov.90.mean)
MAE.error.infer.clust.cov.100.men.15.25.cov.90.mean <- MAE(error.infer.clust.cov.100.men.15.25.cov.90.mean)
ARMSE.error.infer.clust.cov.100.men.15.25.cov.90 <- ARMSE(v1=vector.mean.AD.num.men.true.cov.100.15.25, v2=vector.mean.MAR.cov.90.AD.men.cl.15.25)
MRE.error.infer.clust.cov.100.men.15.25.cov.90.mean <- MRE(error.infer.clust.cov.100.men.15.25.cov.90.mean)
error.infer.clust.cov.100.women.15.25.cov.90.mean <- as.numeric(vector.mean.AD.num.women.true.cov.100.15.25) - as.numeric(vector.mean.MAR.cov.90.AD.women.cl.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.cov.90.mean <- RMSE(error.infer.clust.cov.100.women.15.25.cov.90.mean)
MAE.error.infer.clust.cov.100.women.15.25.cov.90.mean <- MAE(error.infer.clust.cov.100.women.15.25.cov.90.mean)
ARMSE.error.infer.clust.cov.100.women.15.25.cov.90.mean <- ARMSE(v1=vector.mean.AD.num.women.true.cov.100.15.25, v2=vector.mean.MAR.cov.90.AD.women.cl.15.25)
MRE.error.infer.clust.cov.100.women.15.25.cov.90.mean <- MRE(error.infer.clust.cov.100.women.15.25.cov.90.mean)
# Median
error.infer.clust.cov.100.men.15.25.cov.90.med <- as.numeric(vector.med.AD.num.men.true.cov.100.15.25) - as.numeric(vector.med.MAR.cov.90.AD.men.cl.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.cov.90.med <- RMSE(error.infer.clust.cov.100.men.15.25.cov.90.med)
MAE.error.infer.clust.cov.100.men.15.25.cov.90.med <- MAE(error.infer.clust.cov.100.men.15.25.cov.90.med)
ARMSE.error.infer.clust.cov.100.men.15.25.cov.90 <- ARMSE(v1=vector.med.AD.num.men.true.cov.100.15.25, v2=vector.med.MAR.cov.90.AD.men.cl.15.25)
MRE.error.infer.clust.cov.100.men.15.25.cov.90.med <- MRE(error.infer.clust.cov.100.men.15.25.cov.90.med)
error.infer.clust.cov.100.women.15.25.cov.90.med <- as.numeric(vector.med.AD.num.women.true.cov.100.15.25) - as.numeric(vector.med.MAR.cov.90.AD.women.cl.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.cov.90.med <- RMSE(error.infer.clust.cov.100.women.15.25.cov.90.med)
MAE.error.infer.clust.cov.100.women.15.25.cov.90.med <- MAE(error.infer.clust.cov.100.women.15.25.cov.90.med)
ARMSE.error.infer.clust.cov.100.women.15.25.cov.90.med <- ARMSE(v1=vector.med.AD.num.women.true.cov.100.15.25, v2=vector.med.MAR.cov.90.AD.women.cl.15.25)
MRE.error.infer.clust.cov.100.women.15.25.cov.90.med <- MRE(error.infer.clust.cov.100.women.15.25.cov.90.med)
# Standard deviation
error.infer.clust.cov.100.men.15.25.cov.90.sd <- as.numeric(vector.sd.AD.num.men.true.cov.100.15.25) - as.numeric(vector.sd.MAR.cov.90.AD.men.cl.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.cov.90.sd <- RMSE(error.infer.clust.cov.100.men.15.25.cov.90.sd)
MAE.error.infer.clust.cov.100.men.15.25.cov.90.sd <- MAE(error.infer.clust.cov.100.men.15.25.cov.90.sd)
ARMSE.error.infer.clust.cov.100.men.15.25.cov.90 <- ARMSE(v1=vector.sd.AD.num.men.true.cov.100.15.25, v2=vector.sd.MAR.cov.90.AD.men.cl.15.25)
MRE.error.infer.clust.cov.100.men.15.25.cov.90.sd <- MRE(error.infer.clust.cov.100.men.15.25.cov.90.sd)
error.infer.clust.cov.100.women.15.25.cov.90.sd <- as.numeric(vector.sd.AD.num.women.true.cov.100.15.25) - as.numeric(vector.sd.MAR.cov.90.AD.women.cl.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.cov.90.sd <- RMSE(error.infer.clust.cov.100.women.15.25.cov.90.sd)
MAE.error.infer.clust.cov.100.women.15.25.cov.90.sd <- MAE(error.infer.clust.cov.100.women.15.25.cov.90.sd)
ARMSE.error.infer.clust.cov.100.women.15.25.cov.90.sd <- ARMSE(v1=vector.sd.AD.num.women.true.cov.100.15.25, v2=vector.sd.MAR.cov.90.AD.women.cl.15.25)
MRE.error.infer.clust.cov.100.women.15.25.cov.90.sd <- MRE(error.infer.clust.cov.100.women.15.25.cov.90.sd)
# 25.40
# Mean
error.infer.clust.cov.100.men.25.40.cov.90.mean <- as.numeric(vector.mean.AD.num.men.true.cov.100.25.40) - as.numeric(vector.mean.MAR.cov.90.AD.men.cl.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.cov.90.mean <- RMSE(error.infer.clust.cov.100.men.25.40.cov.90.mean)
MAE.error.infer.clust.cov.100.men.25.40.cov.90.mean <- MAE(error.infer.clust.cov.100.men.25.40.cov.90.mean)
ARMSE.error.infer.clust.cov.100.men.25.40.cov.90 <- ARMSE(v1=vector.mean.AD.num.men.true.cov.100.25.40, v2=vector.mean.MAR.cov.90.AD.men.cl.25.40)
MRE.error.infer.clust.cov.100.men.25.40.cov.90.mean <- MRE(error.infer.clust.cov.100.men.25.40.cov.90.mean)
error.infer.clust.cov.100.women.25.40.cov.90.mean <- as.numeric(vector.mean.AD.num.women.true.cov.100.25.40) - as.numeric(vector.mean.MAR.cov.90.AD.women.cl.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.cov.90.mean <- RMSE(error.infer.clust.cov.100.women.25.40.cov.90.mean)
MAE.error.infer.clust.cov.100.women.25.40.cov.90.mean <- MAE(error.infer.clust.cov.100.women.25.40.cov.90.mean)
ARMSE.error.infer.clust.cov.100.women.25.40.cov.90.mean <- ARMSE(v1=vector.mean.AD.num.women.true.cov.100.25.40, v2=vector.mean.MAR.cov.90.AD.women.cl.25.40)
MRE.error.infer.clust.cov.100.women.25.40.cov.90.mean <- MRE(error.infer.clust.cov.100.women.25.40.cov.90.mean)
# Median
error.infer.clust.cov.100.men.25.40.cov.90.med <- as.numeric(vector.med.AD.num.men.true.cov.100.25.40) - as.numeric(vector.med.MAR.cov.90.AD.men.cl.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.cov.90.med <- RMSE(error.infer.clust.cov.100.men.25.40.cov.90.med)
MAE.error.infer.clust.cov.100.men.25.40.cov.90.med <- MAE(error.infer.clust.cov.100.men.25.40.cov.90.med)
ARMSE.error.infer.clust.cov.100.men.25.40.cov.90 <- ARMSE(v1=vector.med.AD.num.men.true.cov.100.25.40, v2=vector.med.MAR.cov.90.AD.men.cl.25.40)
MRE.error.infer.clust.cov.100.men.25.40.cov.90.med <- MRE(error.infer.clust.cov.100.men.25.40.cov.90.med)
error.infer.clust.cov.100.women.25.40.cov.90.med <- as.numeric(vector.med.AD.num.women.true.cov.100.25.40) - as.numeric(vector.med.MAR.cov.90.AD.women.cl.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.cov.90.med <- RMSE(error.infer.clust.cov.100.women.25.40.cov.90.med)
MAE.error.infer.clust.cov.100.women.25.40.cov.90.med <- MAE(error.infer.clust.cov.100.women.25.40.cov.90.med)
ARMSE.error.infer.clust.cov.100.women.25.40.cov.90.med <- ARMSE(v1=vector.med.AD.num.women.true.cov.100.25.40, v2=vector.med.MAR.cov.90.AD.women.cl.25.40)
MRE.error.infer.clust.cov.100.women.25.40.cov.90.med <- MRE(error.infer.clust.cov.100.women.25.40.cov.90.med)
# Standard deviation
error.infer.clust.cov.100.men.25.40.cov.90.sd <- as.numeric(vector.sd.AD.num.men.true.cov.100.25.40) - as.numeric(vector.sd.MAR.cov.90.AD.men.cl.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.cov.90.sd <- RMSE(error.infer.clust.cov.100.men.25.40.cov.90.sd)
MAE.error.infer.clust.cov.100.men.25.40.cov.90.sd <- MAE(error.infer.clust.cov.100.men.25.40.cov.90.sd)
ARMSE.error.infer.clust.cov.100.men.25.40.cov.90 <- ARMSE(v1=vector.sd.AD.num.men.true.cov.100.25.40, v2=vector.sd.MAR.cov.90.AD.men.cl.25.40)
MRE.error.infer.clust.cov.100.men.25.40.cov.90.sd <- MRE(error.infer.clust.cov.100.men.25.40.cov.90.sd)
error.infer.clust.cov.100.women.25.40.cov.90.sd <- as.numeric(vector.sd.AD.num.women.true.cov.100.25.40) - as.numeric(vector.sd.MAR.cov.90.AD.women.cl.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.cov.90.sd <- RMSE(error.infer.clust.cov.100.women.25.40.cov.90.sd)
MAE.error.infer.clust.cov.100.women.25.40.cov.90.sd <- MAE(error.infer.clust.cov.100.women.25.40.cov.90.sd)
ARMSE.error.infer.clust.cov.100.women.25.40.cov.90.sd <- ARMSE(v1=vector.sd.AD.num.women.true.cov.100.25.40, v2=vector.sd.MAR.cov.90.AD.women.cl.25.40)
MRE.error.infer.clust.cov.100.women.25.40.cov.90.sd <- MRE(error.infer.clust.cov.100.women.25.40.cov.90.sd)
# 40.50
# Mean
error.infer.clust.cov.100.men.40.50.cov.90.mean <- as.numeric(vector.mean.AD.num.men.true.cov.100.40.50) - as.numeric(vector.mean.MAR.cov.90.AD.men.cl.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.cov.90.mean <- RMSE(error.infer.clust.cov.100.men.40.50.cov.90.mean)
MAE.error.infer.clust.cov.100.men.40.50.cov.90.mean <- MAE(error.infer.clust.cov.100.men.40.50.cov.90.mean)
ARMSE.error.infer.clust.cov.100.men.40.50.cov.90 <- ARMSE(v1=vector.mean.AD.num.men.true.cov.100.40.50, v2=vector.mean.MAR.cov.90.AD.men.cl.40.50)
MRE.error.infer.clust.cov.100.men.40.50.cov.90.mean <- MRE(error.infer.clust.cov.100.men.40.50.cov.90.mean)
error.infer.clust.cov.100.women.40.50.cov.90.mean <- as.numeric(vector.mean.AD.num.women.true.cov.100.40.50) - as.numeric(vector.mean.MAR.cov.90.AD.women.cl.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.cov.90.mean <- RMSE(error.infer.clust.cov.100.women.40.50.cov.90.mean)
MAE.error.infer.clust.cov.100.women.40.50.cov.90.mean <- MAE(error.infer.clust.cov.100.women.40.50.cov.90.mean)
ARMSE.error.infer.clust.cov.100.women.40.50.cov.90.mean <- ARMSE(v1=vector.mean.AD.num.women.true.cov.100.40.50, v2=vector.mean.MAR.cov.90.AD.women.cl.40.50)
MRE.error.infer.clust.cov.100.women.40.50.cov.90.mean <- MRE(error.infer.clust.cov.100.women.40.50.cov.90.mean)
# Median
error.infer.clust.cov.100.men.40.50.cov.90.med <- as.numeric(vector.med.AD.num.men.true.cov.100.40.50) - as.numeric(vector.med.MAR.cov.90.AD.men.cl.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.cov.90.med <- RMSE(error.infer.clust.cov.100.men.40.50.cov.90.med)
MAE.error.infer.clust.cov.100.men.40.50.cov.90.med <- MAE(error.infer.clust.cov.100.men.40.50.cov.90.med)
ARMSE.error.infer.clust.cov.100.men.40.50.cov.90 <- ARMSE(v1=vector.med.AD.num.men.true.cov.100.40.50, v2=vector.med.MAR.cov.90.AD.men.cl.40.50)
MRE.error.infer.clust.cov.100.men.40.50.cov.90.med <- MRE(error.infer.clust.cov.100.men.40.50.cov.90.med)
error.infer.clust.cov.100.women.40.50.cov.90.med <- as.numeric(vector.med.AD.num.women.true.cov.100.40.50) - as.numeric(vector.med.MAR.cov.90.AD.women.cl.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.cov.90.med <- RMSE(error.infer.clust.cov.100.women.40.50.cov.90.med)
MAE.error.infer.clust.cov.100.women.40.50.cov.90.med <- MAE(error.infer.clust.cov.100.women.40.50.cov.90.med)
ARMSE.error.infer.clust.cov.100.women.40.50.cov.90.med <- ARMSE(v1=vector.med.AD.num.women.true.cov.100.40.50, v2=vector.med.MAR.cov.90.AD.women.cl.40.50)
MRE.error.infer.clust.cov.100.women.40.50.cov.90.med <- MRE(error.infer.clust.cov.100.women.40.50.cov.90.med)
# Standard deviation
error.infer.clust.cov.100.men.40.50.cov.90.sd <- as.numeric(vector.sd.AD.num.men.true.cov.100.40.50) - as.numeric(vector.sd.MAR.cov.90.AD.men.cl.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.cov.90.sd <- RMSE(error.infer.clust.cov.100.men.40.50.cov.90.sd)
MAE.error.infer.clust.cov.100.men.40.50.cov.90.sd <- MAE(error.infer.clust.cov.100.men.40.50.cov.90.sd)
ARMSE.error.infer.clust.cov.100.men.40.50.cov.90 <- ARMSE(v1=vector.sd.AD.num.men.true.cov.100.40.50, v2=vector.sd.MAR.cov.90.AD.men.cl.40.50)
MRE.error.infer.clust.cov.100.men.40.50.cov.90.sd <- MRE(error.infer.clust.cov.100.men.40.50.cov.90.sd)
error.infer.clust.cov.100.women.40.50.cov.90.sd <- as.numeric(vector.sd.AD.num.women.true.cov.100.40.50) - as.numeric(vector.sd.MAR.cov.90.AD.women.cl.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.cov.90.sd <- RMSE(error.infer.clust.cov.100.women.40.50.cov.90.sd)
MAE.error.infer.clust.cov.100.women.40.50.cov.90.sd <- MAE(error.infer.clust.cov.100.women.40.50.cov.90.sd)
ARMSE.error.infer.clust.cov.100.women.40.50.cov.90.sd <- ARMSE(v1=vector.sd.AD.num.women.true.cov.100.40.50, v2=vector.sd.MAR.cov.90.AD.women.cl.40.50)
MRE.error.infer.clust.cov.100.women.40.50.cov.90.sd <- MRE(error.infer.clust.cov.100.women.40.50.cov.90.sd)
# Cov 95
# 15.25
# Mean
error.infer.clust.cov.100.men.15.25.cov.95.mean <- as.numeric(vector.mean.AD.num.men.true.cov.100.15.25) - as.numeric(vector.mean.MAR.cov.95.AD.men.cl.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.cov.95.mean <- RMSE(error.infer.clust.cov.100.men.15.25.cov.95.mean)
MAE.error.infer.clust.cov.100.men.15.25.cov.95.mean <- MAE(error.infer.clust.cov.100.men.15.25.cov.95.mean)
ARMSE.error.infer.clust.cov.100.men.15.25.cov.95 <- ARMSE(v1=vector.mean.AD.num.men.true.cov.100.15.25, v2=vector.mean.MAR.cov.95.AD.men.cl.15.25)
MRE.error.infer.clust.cov.100.men.15.25.cov.95.mean <- MRE(error.infer.clust.cov.100.men.15.25.cov.95.mean)
error.infer.clust.cov.100.women.15.25.cov.95.mean <- as.numeric(vector.mean.AD.num.women.true.cov.100.15.25) - as.numeric(vector.mean.MAR.cov.95.AD.women.cl.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.cov.95.mean <- RMSE(error.infer.clust.cov.100.women.15.25.cov.95.mean)
MAE.error.infer.clust.cov.100.women.15.25.cov.95.mean <- MAE(error.infer.clust.cov.100.women.15.25.cov.95.mean)
ARMSE.error.infer.clust.cov.100.women.15.25.cov.95.mean <- ARMSE(v1=vector.mean.AD.num.women.true.cov.100.15.25, v2=vector.mean.MAR.cov.95.AD.women.cl.15.25)
MRE.error.infer.clust.cov.100.women.15.25.cov.95.mean <- MRE(error.infer.clust.cov.100.women.15.25.cov.95.mean)
# Median
error.infer.clust.cov.100.men.15.25.cov.95.med <- as.numeric(vector.med.AD.num.men.true.cov.100.15.25) - as.numeric(vector.med.MAR.cov.95.AD.men.cl.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.cov.95.med <- RMSE(error.infer.clust.cov.100.men.15.25.cov.95.med)
MAE.error.infer.clust.cov.100.men.15.25.cov.95.med <- MAE(error.infer.clust.cov.100.men.15.25.cov.95.med)
ARMSE.error.infer.clust.cov.100.men.15.25.cov.95 <- ARMSE(v1=vector.med.AD.num.men.true.cov.100.15.25, v2=vector.med.MAR.cov.95.AD.men.cl.15.25)
MRE.error.infer.clust.cov.100.men.15.25.cov.95.med <- MRE(error.infer.clust.cov.100.men.15.25.cov.95.med)
error.infer.clust.cov.100.women.15.25.cov.95.med <- as.numeric(vector.med.AD.num.women.true.cov.100.15.25) - as.numeric(vector.med.MAR.cov.95.AD.women.cl.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.cov.95.med <- RMSE(error.infer.clust.cov.100.women.15.25.cov.95.med)
MAE.error.infer.clust.cov.100.women.15.25.cov.95.med <- MAE(error.infer.clust.cov.100.women.15.25.cov.95.med)
ARMSE.error.infer.clust.cov.100.women.15.25.cov.95.med <- ARMSE(v1=vector.med.AD.num.women.true.cov.100.15.25, v2=vector.med.MAR.cov.95.AD.women.cl.15.25)
MRE.error.infer.clust.cov.100.women.15.25.cov.95.med <- MRE(error.infer.clust.cov.100.women.15.25.cov.95.med)
# Standard deviation
error.infer.clust.cov.100.men.15.25.cov.95.sd <- as.numeric(vector.sd.AD.num.men.true.cov.100.15.25) - as.numeric(vector.sd.MAR.cov.95.AD.men.cl.15.25)
RMSE.error.infer.clust.cov.100.men.15.25.cov.95.sd <- RMSE(error.infer.clust.cov.100.men.15.25.cov.95.sd)
MAE.error.infer.clust.cov.100.men.15.25.cov.95.sd <- MAE(error.infer.clust.cov.100.men.15.25.cov.95.sd)
ARMSE.error.infer.clust.cov.100.men.15.25.cov.95 <- ARMSE(v1=vector.sd.AD.num.men.true.cov.100.15.25, v2=vector.sd.MAR.cov.95.AD.men.cl.15.25)
MRE.error.infer.clust.cov.100.men.15.25.cov.95.sd <- MRE(error.infer.clust.cov.100.men.15.25.cov.95.sd)
error.infer.clust.cov.100.women.15.25.cov.95.sd <- as.numeric(vector.sd.AD.num.women.true.cov.100.15.25) - as.numeric(vector.sd.MAR.cov.95.AD.women.cl.15.25)
RMSE.error.infer.clust.cov.100.women.15.25.cov.95.sd <- RMSE(error.infer.clust.cov.100.women.15.25.cov.95.sd)
MAE.error.infer.clust.cov.100.women.15.25.cov.95.sd <- MAE(error.infer.clust.cov.100.women.15.25.cov.95.sd)
ARMSE.error.infer.clust.cov.100.women.15.25.cov.95.sd <- ARMSE(v1=vector.sd.AD.num.women.true.cov.100.15.25, v2=vector.sd.MAR.cov.95.AD.women.cl.15.25)
MRE.error.infer.clust.cov.100.women.15.25.cov.95.sd <- MRE(error.infer.clust.cov.100.women.15.25.cov.95.sd)
# 25.40
# Mean
error.infer.clust.cov.100.men.25.40.cov.95.mean <- as.numeric(vector.mean.AD.num.men.true.cov.100.25.40) - as.numeric(vector.mean.MAR.cov.95.AD.men.cl.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.cov.95.mean <- RMSE(error.infer.clust.cov.100.men.25.40.cov.95.mean)
MAE.error.infer.clust.cov.100.men.25.40.cov.95.mean <- MAE(error.infer.clust.cov.100.men.25.40.cov.95.mean)
ARMSE.error.infer.clust.cov.100.men.25.40.cov.95 <- ARMSE(v1=vector.mean.AD.num.men.true.cov.100.25.40, v2=vector.mean.MAR.cov.95.AD.men.cl.25.40)
MRE.error.infer.clust.cov.100.men.25.40.cov.95.mean <- MRE(error.infer.clust.cov.100.men.25.40.cov.95.mean)
error.infer.clust.cov.100.women.25.40.cov.95.mean <- as.numeric(vector.mean.AD.num.women.true.cov.100.25.40) - as.numeric(vector.mean.MAR.cov.95.AD.women.cl.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.cov.95.mean <- RMSE(error.infer.clust.cov.100.women.25.40.cov.95.mean)
MAE.error.infer.clust.cov.100.women.25.40.cov.95.mean <- MAE(error.infer.clust.cov.100.women.25.40.cov.95.mean)
ARMSE.error.infer.clust.cov.100.women.25.40.cov.95.mean <- ARMSE(v1=vector.mean.AD.num.women.true.cov.100.25.40, v2=vector.mean.MAR.cov.95.AD.women.cl.25.40)
MRE.error.infer.clust.cov.100.women.25.40.cov.95.mean <- MRE(error.infer.clust.cov.100.women.25.40.cov.95.mean)
# Median
error.infer.clust.cov.100.men.25.40.cov.95.med <- as.numeric(vector.med.AD.num.men.true.cov.100.25.40) - as.numeric(vector.med.MAR.cov.95.AD.men.cl.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.cov.95.med <- RMSE(error.infer.clust.cov.100.men.25.40.cov.95.med)
MAE.error.infer.clust.cov.100.men.25.40.cov.95.med <- MAE(error.infer.clust.cov.100.men.25.40.cov.95.med)
ARMSE.error.infer.clust.cov.100.men.25.40.cov.95 <- ARMSE(v1=vector.med.AD.num.men.true.cov.100.25.40, v2=vector.med.MAR.cov.95.AD.men.cl.25.40)
MRE.error.infer.clust.cov.100.men.25.40.cov.95.med <- MRE(error.infer.clust.cov.100.men.25.40.cov.95.med)
error.infer.clust.cov.100.women.25.40.cov.95.med <- as.numeric(vector.med.AD.num.women.true.cov.100.25.40) - as.numeric(vector.med.MAR.cov.95.AD.women.cl.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.cov.95.med <- RMSE(error.infer.clust.cov.100.women.25.40.cov.95.med)
MAE.error.infer.clust.cov.100.women.25.40.cov.95.med <- MAE(error.infer.clust.cov.100.women.25.40.cov.95.med)
ARMSE.error.infer.clust.cov.100.women.25.40.cov.95.med <- ARMSE(v1=vector.med.AD.num.women.true.cov.100.25.40, v2=vector.med.MAR.cov.95.AD.women.cl.25.40)
MRE.error.infer.clust.cov.100.women.25.40.cov.95.med <- MRE(error.infer.clust.cov.100.women.25.40.cov.95.med)
# Standard deviation
error.infer.clust.cov.100.men.25.40.cov.95.sd <- as.numeric(vector.sd.AD.num.men.true.cov.100.25.40) - as.numeric(vector.sd.MAR.cov.95.AD.men.cl.25.40)
RMSE.error.infer.clust.cov.100.men.25.40.cov.95.sd <- RMSE(error.infer.clust.cov.100.men.25.40.cov.95.sd)
MAE.error.infer.clust.cov.100.men.25.40.cov.95.sd <- MAE(error.infer.clust.cov.100.men.25.40.cov.95.sd)
ARMSE.error.infer.clust.cov.100.men.25.40.cov.95 <- ARMSE(v1=vector.sd.AD.num.men.true.cov.100.25.40, v2=vector.sd.MAR.cov.95.AD.men.cl.25.40)
MRE.error.infer.clust.cov.100.men.25.40.cov.95.sd <- MRE(error.infer.clust.cov.100.men.25.40.cov.95.sd)
error.infer.clust.cov.100.women.25.40.cov.95.sd <- as.numeric(vector.sd.AD.num.women.true.cov.100.25.40) - as.numeric(vector.sd.MAR.cov.95.AD.women.cl.25.40)
RMSE.error.infer.clust.cov.100.women.25.40.cov.95.sd <- RMSE(error.infer.clust.cov.100.women.25.40.cov.95.sd)
MAE.error.infer.clust.cov.100.women.25.40.cov.95.sd <- MAE(error.infer.clust.cov.100.women.25.40.cov.95.sd)
ARMSE.error.infer.clust.cov.100.women.25.40.cov.95.sd <- ARMSE(v1=vector.sd.AD.num.women.true.cov.100.25.40, v2=vector.sd.MAR.cov.95.AD.women.cl.25.40)
MRE.error.infer.clust.cov.100.women.25.40.cov.95.sd <- MRE(error.infer.clust.cov.100.women.25.40.cov.95.sd)
# 40.50
# Mean
error.infer.clust.cov.100.men.40.50.cov.95.mean <- as.numeric(vector.mean.AD.num.men.true.cov.100.40.50) - as.numeric(vector.mean.MAR.cov.95.AD.men.cl.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.cov.95.mean <- RMSE(error.infer.clust.cov.100.men.40.50.cov.95.mean)
MAE.error.infer.clust.cov.100.men.40.50.cov.95.mean <- MAE(error.infer.clust.cov.100.men.40.50.cov.95.mean)
ARMSE.error.infer.clust.cov.100.men.40.50.cov.95 <- ARMSE(v1=vector.mean.AD.num.men.true.cov.100.40.50, v2=vector.mean.MAR.cov.95.AD.men.cl.40.50)
MRE.error.infer.clust.cov.100.men.40.50.cov.95.mean <- MRE(error.infer.clust.cov.100.men.40.50.cov.95.mean)
error.infer.clust.cov.100.women.40.50.cov.95.mean <- as.numeric(vector.mean.AD.num.women.true.cov.100.40.50) - as.numeric(vector.mean.MAR.cov.95.AD.women.cl.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.cov.95.mean <- RMSE(error.infer.clust.cov.100.women.40.50.cov.95.mean)
MAE.error.infer.clust.cov.100.women.40.50.cov.95.mean <- MAE(error.infer.clust.cov.100.women.40.50.cov.95.mean)
ARMSE.error.infer.clust.cov.100.women.40.50.cov.95.mean <- ARMSE(v1=vector.mean.AD.num.women.true.cov.100.40.50, v2=vector.mean.MAR.cov.95.AD.women.cl.40.50)
MRE.error.infer.clust.cov.100.women.40.50.cov.95.mean <- MRE(error.infer.clust.cov.100.women.40.50.cov.95.mean)
# Median
error.infer.clust.cov.100.men.40.50.cov.95.med <- as.numeric(vector.med.AD.num.men.true.cov.100.40.50) - as.numeric(vector.med.MAR.cov.95.AD.men.cl.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.cov.95.med <- RMSE(error.infer.clust.cov.100.men.40.50.cov.95.med)
MAE.error.infer.clust.cov.100.men.40.50.cov.95.med <- MAE(error.infer.clust.cov.100.men.40.50.cov.95.med)
ARMSE.error.infer.clust.cov.100.men.40.50.cov.95 <- ARMSE(v1=vector.med.AD.num.men.true.cov.100.40.50, v2=vector.med.MAR.cov.95.AD.men.cl.40.50)
MRE.error.infer.clust.cov.100.men.40.50.cov.95.med <- MRE(error.infer.clust.cov.100.men.40.50.cov.95.med)
error.infer.clust.cov.100.women.40.50.cov.95.med <- as.numeric(vector.med.AD.num.women.true.cov.100.40.50) - as.numeric(vector.med.MAR.cov.95.AD.women.cl.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.cov.95.med <- RMSE(error.infer.clust.cov.100.women.40.50.cov.95.med)
MAE.error.infer.clust.cov.100.women.40.50.cov.95.med <- MAE(error.infer.clust.cov.100.women.40.50.cov.95.med)
ARMSE.error.infer.clust.cov.100.women.40.50.cov.95.med <- ARMSE(v1=vector.med.AD.num.women.true.cov.100.40.50, v2=vector.med.MAR.cov.95.AD.women.cl.40.50)
MRE.error.infer.clust.cov.100.women.40.50.cov.95.med <- MRE(error.infer.clust.cov.100.women.40.50.cov.95.med)
# Standard deviation
error.infer.clust.cov.100.men.40.50.cov.95.sd <- as.numeric(vector.sd.AD.num.men.true.cov.100.40.50) - as.numeric(vector.sd.MAR.cov.95.AD.men.cl.40.50)
RMSE.error.infer.clust.cov.100.men.40.50.cov.95.sd <- RMSE(error.infer.clust.cov.100.men.40.50.cov.95.sd)
MAE.error.infer.clust.cov.100.men.40.50.cov.95.sd <- MAE(error.infer.clust.cov.100.men.40.50.cov.95.sd)
ARMSE.error.infer.clust.cov.100.men.40.50.cov.95 <- ARMSE(v1=vector.sd.AD.num.men.true.cov.100.40.50, v2=vector.sd.MAR.cov.95.AD.men.cl.40.50)
MRE.error.infer.clust.cov.100.men.40.50.cov.95.sd <- MRE(error.infer.clust.cov.100.men.40.50.cov.95.sd)
error.infer.clust.cov.100.women.40.50.cov.95.sd <- as.numeric(vector.sd.AD.num.women.true.cov.100.40.50) - as.numeric(vector.sd.MAR.cov.95.AD.women.cl.40.50)
RMSE.error.infer.clust.cov.100.women.40.50.cov.95.sd <- RMSE(error.infer.clust.cov.100.women.40.50.cov.95.sd)
MAE.error.infer.clust.cov.100.women.40.50.cov.95.sd <- MAE(error.infer.clust.cov.100.women.40.50.cov.95.sd)
ARMSE.error.infer.clust.cov.100.women.40.50.cov.95.sd <- ARMSE(v1=vector.sd.AD.num.women.true.cov.100.40.50, v2=vector.sd.MAR.cov.95.AD.women.cl.40.50)
MRE.error.infer.clust.cov.100.women.40.50.cov.95.sd <- MRE(error.infer.clust.cov.100.women.40.50.cov.95.sd)# Figures --------------------------------------
# 15 - 25
RMSE.error.infer.clust.cov.100.women.15.25.AD.mean <- data.frame(x=c("35", "40", "45",
"50", "55", "60",
"65", "70", "75",
"80", "85", "90",
"95"),
F = c(RMSE.error.infer.clust.cov.100.women.15.25.cov.35.mean, RMSE.error.infer.clust.cov.100.women.15.25.cov.40.mean,
RMSE.error.infer.clust.cov.100.women.15.25.cov.45.mean, RMSE.error.infer.clust.cov.100.women.15.25.cov.50.mean,
RMSE.error.infer.clust.cov.100.women.15.25.cov.55.mean, RMSE.error.infer.clust.cov.100.women.15.25.cov.60.mean,
RMSE.error.infer.clust.cov.100.women.15.25.cov.65.mean, RMSE.error.infer.clust.cov.100.women.15.25.cov.70.mean,
RMSE.error.infer.clust.cov.100.women.15.25.cov.75.mean, RMSE.error.infer.clust.cov.100.women.15.25.cov.80.mean,
RMSE.error.infer.clust.cov.100.women.15.25.cov.85.mean, RMSE.error.infer.clust.cov.100.women.15.25.cov.90.mean,
RMSE.error.infer.clust.cov.100.women.15.25.cov.95.mean))
plot.RMSE.error.infer.clust.cov.100.women.15.25.AD.mean <- ggplot(RMSE.error.infer.clust.cov.100.women.15.25.AD.mean, aes(x = x, y = F)) +
geom_point(size = 4) +
ggtitle("Error for mean age difference for women in 15 - 25 - MCAR") +
xlab("Sequence sampling coverage") + ylab("Error value")
# plot.RMSE.error.infer.clust.cov.100.women.15.25.AD.meanRMSE.error.infer.clust.cov.100.men.15.25.AD.mean <- data.frame(x=c("35", "40", "45",
"50", "55", "60",
"65", "70", "75",
"80", "85", "90",
"95"),
F = c(RMSE.error.infer.clust.cov.100.men.15.25.cov.35.mean, RMSE.error.infer.clust.cov.100.men.15.25.cov.40.mean,
RMSE.error.infer.clust.cov.100.men.15.25.cov.45.mean, RMSE.error.infer.clust.cov.100.men.15.25.cov.50.mean,
RMSE.error.infer.clust.cov.100.men.15.25.cov.55.mean, RMSE.error.infer.clust.cov.100.men.15.25.cov.60.mean,
RMSE.error.infer.clust.cov.100.men.15.25.cov.65.mean, RMSE.error.infer.clust.cov.100.men.15.25.cov.70.mean,
RMSE.error.infer.clust.cov.100.men.15.25.cov.75.mean, RMSE.error.infer.clust.cov.100.men.15.25.cov.80.mean,
RMSE.error.infer.clust.cov.100.men.15.25.cov.85.mean, RMSE.error.infer.clust.cov.100.men.15.25.cov.90.mean,
RMSE.error.infer.clust.cov.100.men.15.25.cov.95.mean))
plot.RMSE.error.infer.clust.cov.100.men.15.25.AD.mean <- ggplot(RMSE.error.infer.clust.cov.100.men.15.25.AD.mean, aes(x = x, y = F)) +
geom_point(size = 4) +
ggtitle("Error for mean age difference for men in 15 - 25 - MCAR") +
xlab("Sequence sampling coverage") + ylab("Error value")
# plot.RMSE.error.infer.clust.cov.100.men.15.25.AD.meanRMSE.error.infer.clust.cov.100.women.15.25.AD.med <- data.frame(x=c("35", "40", "45",
"50", "55", "60",
"65", "70", "75",
"80", "85", "90",
"95"),
F = c(RMSE.error.infer.clust.cov.100.women.15.25.cov.35.med, RMSE.error.infer.clust.cov.100.women.15.25.cov.40.med,
RMSE.error.infer.clust.cov.100.women.15.25.cov.45.med, RMSE.error.infer.clust.cov.100.women.15.25.cov.50.med,
RMSE.error.infer.clust.cov.100.women.15.25.cov.55.med, RMSE.error.infer.clust.cov.100.women.15.25.cov.60.med,
RMSE.error.infer.clust.cov.100.women.15.25.cov.65.med, RMSE.error.infer.clust.cov.100.women.15.25.cov.70.med,
RMSE.error.infer.clust.cov.100.women.15.25.cov.75.med, RMSE.error.infer.clust.cov.100.women.15.25.cov.80.med,
RMSE.error.infer.clust.cov.100.women.15.25.cov.85.med, RMSE.error.infer.clust.cov.100.women.15.25.cov.90.med,
RMSE.error.infer.clust.cov.100.women.15.25.cov.95.med))
plot.RMSE.error.infer.clust.cov.100.women.15.25.AD.med <- ggplot(RMSE.error.infer.clust.cov.100.women.15.25.AD.med, aes(x = x, y = F)) +
geom_point(size = 4) +
ggtitle("Error for median age difference for women in 15 - 25 - MCAR") +
xlab("Sequence sampling coverage") + ylab("Error value")
# plot.RMSE.error.infer.clust.cov.100.women.15.25.AD.medRMSE.error.infer.clust.cov.100.men.15.25.AD.med <- data.frame(x=c("35", "40", "45",
"50", "55", "60",
"65", "70", "75",
"80", "85", "90",
"95"),
F = c(RMSE.error.infer.clust.cov.100.men.15.25.cov.35.med, RMSE.error.infer.clust.cov.100.men.15.25.cov.40.med,
RMSE.error.infer.clust.cov.100.men.15.25.cov.45.med, RMSE.error.infer.clust.cov.100.men.15.25.cov.50.med,
RMSE.error.infer.clust.cov.100.men.15.25.cov.55.med, RMSE.error.infer.clust.cov.100.men.15.25.cov.60.med,
RMSE.error.infer.clust.cov.100.men.15.25.cov.65.med, RMSE.error.infer.clust.cov.100.men.15.25.cov.70.med,
RMSE.error.infer.clust.cov.100.men.15.25.cov.75.med, RMSE.error.infer.clust.cov.100.men.15.25.cov.80.med,
RMSE.error.infer.clust.cov.100.men.15.25.cov.85.med, RMSE.error.infer.clust.cov.100.men.15.25.cov.90.med,
RMSE.error.infer.clust.cov.100.men.15.25.cov.95.med))
plot.RMSE.error.infer.clust.cov.100.men.15.25.AD.med <- ggplot(RMSE.error.infer.clust.cov.100.men.15.25.AD.med, aes(x = x, y = F)) +
geom_point(size = 4) +
ggtitle("Error for median age difference for men in 15 - 25 - MCAR") +
xlab("Sequence sampling coverage") + ylab("Error value")
# plot.RMSE.error.infer.clust.cov.100.men.15.25.AD.medRMSE.error.infer.clust.cov.100.women.15.25.AD.sd <- data.frame(x=c("35", "40", "45",
"50", "55", "60",
"65", "70", "75",
"80", "85", "90",
"95"),
F = c(RMSE.error.infer.clust.cov.100.women.15.25.cov.35.sd, RMSE.error.infer.clust.cov.100.women.15.25.cov.40.sd,
RMSE.error.infer.clust.cov.100.women.15.25.cov.45.sd, RMSE.error.infer.clust.cov.100.women.15.25.cov.50.sd,
RMSE.error.infer.clust.cov.100.women.15.25.cov.55.sd, RMSE.error.infer.clust.cov.100.women.15.25.cov.60.sd,
RMSE.error.infer.clust.cov.100.women.15.25.cov.65.sd, RMSE.error.infer.clust.cov.100.women.15.25.cov.70.sd,
RMSE.error.infer.clust.cov.100.women.15.25.cov.75.sd, RMSE.error.infer.clust.cov.100.women.15.25.cov.80.sd,
RMSE.error.infer.clust.cov.100.women.15.25.cov.85.sd, RMSE.error.infer.clust.cov.100.women.15.25.cov.90.sd,
RMSE.error.infer.clust.cov.100.women.15.25.cov.95.sd))
plot.RMSE.error.infer.clust.cov.100.women.15.25.AD.sd <- ggplot(RMSE.error.infer.clust.cov.100.women.15.25.AD.sd, aes(x = x, y = F)) +
geom_point(size = 4) +
ggtitle("Error for SD age difference for women in 15 - 25 - MCAR") +
xlab("Sequence sampling coverage") + ylab("Error value")
# plot.RMSE.error.infer.clust.cov.100.women.15.25.AD.sdRMSE.error.infer.clust.cov.100.men.15.25.AD.sd <- data.frame(x=c("35", "40", "45",
"50", "55", "60",
"65", "70", "75",
"80", "85", "90",
"95"),
F = c(RMSE.error.infer.clust.cov.100.men.15.25.cov.35.sd, RMSE.error.infer.clust.cov.100.men.15.25.cov.40.sd,
RMSE.error.infer.clust.cov.100.men.15.25.cov.45.sd, RMSE.error.infer.clust.cov.100.men.15.25.cov.50.sd,
RMSE.error.infer.clust.cov.100.men.15.25.cov.55.sd, RMSE.error.infer.clust.cov.100.men.15.25.cov.60.sd,
RMSE.error.infer.clust.cov.100.men.15.25.cov.65.sd, RMSE.error.infer.clust.cov.100.men.15.25.cov.70.sd,
RMSE.error.infer.clust.cov.100.men.15.25.cov.75.sd, RMSE.error.infer.clust.cov.100.men.15.25.cov.80.sd,
RMSE.error.infer.clust.cov.100.men.15.25.cov.85.sd, RMSE.error.infer.clust.cov.100.men.15.25.cov.90.sd,
RMSE.error.infer.clust.cov.100.men.15.25.cov.95.sd))
plot.RMSE.error.infer.clust.cov.100.men.15.25.AD.sd <- ggplot(RMSE.error.infer.clust.cov.100.men.15.25.AD.sd, aes(x = x, y = F)) +
geom_point(size = 4) +
ggtitle("Error for SD age difference for men in 15 - 25 - MCAR") +
xlab("Sequence sampling coverage") + ylab("Error value")
# plot.RMSE.error.infer.clust.cov.100.men.15.25.AD.sd# 25 - 40
RMSE.error.infer.clust.cov.100.women.25.40.AD.mean <- data.frame(x=c("35", "40", "45",
"50", "55", "60",
"65", "70", "75",
"80", "85", "90",
"95"),
F = c(RMSE.error.infer.clust.cov.100.women.25.40.cov.35.mean, RMSE.error.infer.clust.cov.100.women.25.40.cov.40.mean,
RMSE.error.infer.clust.cov.100.women.25.40.cov.45.mean, RMSE.error.infer.clust.cov.100.women.25.40.cov.50.mean,
RMSE.error.infer.clust.cov.100.women.25.40.cov.55.mean, RMSE.error.infer.clust.cov.100.women.25.40.cov.60.mean,
RMSE.error.infer.clust.cov.100.women.25.40.cov.65.mean, RMSE.error.infer.clust.cov.100.women.25.40.cov.70.mean,
RMSE.error.infer.clust.cov.100.women.25.40.cov.75.mean, RMSE.error.infer.clust.cov.100.women.25.40.cov.80.mean,
RMSE.error.infer.clust.cov.100.women.25.40.cov.85.mean, RMSE.error.infer.clust.cov.100.women.25.40.cov.90.mean,
RMSE.error.infer.clust.cov.100.women.25.40.cov.95.mean))
plot.RMSE.error.infer.clust.cov.100.women.25.40.AD.mean <- ggplot(RMSE.error.infer.clust.cov.100.women.25.40.AD.mean, aes(x = x, y = F)) +
geom_point(size = 4) +
ggtitle("Error for mean age difference for women in 25 - 40 - MCAR") +
xlab("Sequence sampling coverage") + ylab("Error value")
# plot.RMSE.error.infer.clust.cov.100.women.25.40.AD.meanRMSE.error.infer.clust.cov.100.men.25.40.AD.mean <- data.frame(x=c("35", "40", "45",
"50", "55", "60",
"65", "70", "75",
"80", "85", "90",
"95"),
F = c(RMSE.error.infer.clust.cov.100.men.25.40.cov.35.mean, RMSE.error.infer.clust.cov.100.men.25.40.cov.40.mean,
RMSE.error.infer.clust.cov.100.men.25.40.cov.45.mean, RMSE.error.infer.clust.cov.100.men.25.40.cov.50.mean,
RMSE.error.infer.clust.cov.100.men.25.40.cov.55.mean, RMSE.error.infer.clust.cov.100.men.25.40.cov.60.mean,
RMSE.error.infer.clust.cov.100.men.25.40.cov.65.mean, RMSE.error.infer.clust.cov.100.men.25.40.cov.70.mean,
RMSE.error.infer.clust.cov.100.men.25.40.cov.75.mean, RMSE.error.infer.clust.cov.100.men.25.40.cov.80.mean,
RMSE.error.infer.clust.cov.100.men.25.40.cov.85.mean, RMSE.error.infer.clust.cov.100.men.25.40.cov.90.mean,
RMSE.error.infer.clust.cov.100.men.25.40.cov.95.mean))
plot.RMSE.error.infer.clust.cov.100.men.25.40.AD.mean <- ggplot(RMSE.error.infer.clust.cov.100.men.25.40.AD.mean, aes(x = x, y = F)) +
geom_point(size = 4) +
ggtitle("Error for mean age difference for men in 25 - 40 - MCAR") +
xlab("Sequence sampling coverage") + ylab("Error value")
# plot.RMSE.error.infer.clust.cov.100.men.25.40.AD.meanRMSE.error.infer.clust.cov.100.women.25.40.AD.med <- data.frame(x=c("35", "40", "45",
"50", "55", "60",
"65", "70", "75",
"80", "85", "90",
"95"),
F = c(RMSE.error.infer.clust.cov.100.women.25.40.cov.35.med, RMSE.error.infer.clust.cov.100.women.25.40.cov.40.med,
RMSE.error.infer.clust.cov.100.women.25.40.cov.45.med, RMSE.error.infer.clust.cov.100.women.25.40.cov.50.med,
RMSE.error.infer.clust.cov.100.women.25.40.cov.55.med, RMSE.error.infer.clust.cov.100.women.25.40.cov.60.med,
RMSE.error.infer.clust.cov.100.women.25.40.cov.65.med, RMSE.error.infer.clust.cov.100.women.25.40.cov.70.med,
RMSE.error.infer.clust.cov.100.women.25.40.cov.75.med, RMSE.error.infer.clust.cov.100.women.25.40.cov.80.med,
RMSE.error.infer.clust.cov.100.women.25.40.cov.85.med, RMSE.error.infer.clust.cov.100.women.25.40.cov.90.med,
RMSE.error.infer.clust.cov.100.women.25.40.cov.95.med))
plot.RMSE.error.infer.clust.cov.100.women.25.40.AD.med <- ggplot(RMSE.error.infer.clust.cov.100.women.25.40.AD.med, aes(x = x, y = F)) +
geom_point(size = 4) +
ggtitle("Error for median age difference for women in 25 - 40 - MCAR") +
xlab("Sequence sampling coverage") + ylab("Error value")
# plot.RMSE.error.infer.clust.cov.100.women.25.40.AD.medRMSE.error.infer.clust.cov.100.men.25.40.AD.med <- data.frame(x=c("35", "40", "45",
"50", "55", "60",
"65", "70", "75",
"80", "85", "90",
"95"),
F = c(RMSE.error.infer.clust.cov.100.men.25.40.cov.35.med, RMSE.error.infer.clust.cov.100.men.25.40.cov.40.med,
RMSE.error.infer.clust.cov.100.men.25.40.cov.45.med, RMSE.error.infer.clust.cov.100.men.25.40.cov.50.med,
RMSE.error.infer.clust.cov.100.men.25.40.cov.55.med, RMSE.error.infer.clust.cov.100.men.25.40.cov.60.med,
RMSE.error.infer.clust.cov.100.men.25.40.cov.65.med, RMSE.error.infer.clust.cov.100.men.25.40.cov.70.med,
RMSE.error.infer.clust.cov.100.men.25.40.cov.75.med, RMSE.error.infer.clust.cov.100.men.25.40.cov.80.med,
RMSE.error.infer.clust.cov.100.men.25.40.cov.85.med, RMSE.error.infer.clust.cov.100.men.25.40.cov.90.med,
RMSE.error.infer.clust.cov.100.men.25.40.cov.95.med))
plot.RMSE.error.infer.clust.cov.100.men.25.40.AD.med <- ggplot(RMSE.error.infer.clust.cov.100.men.25.40.AD.med, aes(x = x, y = F)) +
geom_point(size = 4) +
ggtitle("Error for median age difference for men in 25 - 40 - MCAR") +
xlab("Sequence sampling coverage") + ylab("Error value")
# plot.RMSE.error.infer.clust.cov.100.men.25.40.AD.medRMSE.error.infer.clust.cov.100.women.25.40.AD.sd <- data.frame(x=c("35", "40", "45",
"50", "55", "60",
"65", "70", "75",
"80", "85", "90",
"95"),
F = c(RMSE.error.infer.clust.cov.100.women.25.40.cov.35.sd, RMSE.error.infer.clust.cov.100.women.25.40.cov.40.sd,
RMSE.error.infer.clust.cov.100.women.25.40.cov.45.sd, RMSE.error.infer.clust.cov.100.women.25.40.cov.50.sd,
RMSE.error.infer.clust.cov.100.women.25.40.cov.55.sd, RMSE.error.infer.clust.cov.100.women.25.40.cov.60.sd,
RMSE.error.infer.clust.cov.100.women.25.40.cov.65.sd, RMSE.error.infer.clust.cov.100.women.25.40.cov.70.sd,
RMSE.error.infer.clust.cov.100.women.25.40.cov.75.sd, RMSE.error.infer.clust.cov.100.women.25.40.cov.80.sd,
RMSE.error.infer.clust.cov.100.women.25.40.cov.85.sd, RMSE.error.infer.clust.cov.100.women.25.40.cov.90.sd,
RMSE.error.infer.clust.cov.100.women.25.40.cov.95.sd))
plot.RMSE.error.infer.clust.cov.100.women.25.40.AD.sd <- ggplot(RMSE.error.infer.clust.cov.100.women.25.40.AD.sd, aes(x = x, y = F)) +
geom_point(size = 4) +
ggtitle("Error for SD age difference for women in 25 - 40 - MCAR") +
xlab("Sequence sampling coverage") + ylab("Error value")
# plot.RMSE.error.infer.clust.cov.100.women.25.40.AD.sdRMSE.error.infer.clust.cov.100.men.25.40.AD.sd <- data.frame(x=c("35", "40", "45",
"50", "55", "60",
"65", "70", "75",
"80", "85", "90",
"95"),
F = c(RMSE.error.infer.clust.cov.100.men.25.40.cov.35.sd, RMSE.error.infer.clust.cov.100.men.25.40.cov.40.sd,
RMSE.error.infer.clust.cov.100.men.25.40.cov.45.sd, RMSE.error.infer.clust.cov.100.men.25.40.cov.50.sd,
RMSE.error.infer.clust.cov.100.men.25.40.cov.55.sd, RMSE.error.infer.clust.cov.100.men.25.40.cov.60.sd,
RMSE.error.infer.clust.cov.100.men.25.40.cov.65.sd, RMSE.error.infer.clust.cov.100.men.25.40.cov.70.sd,
RMSE.error.infer.clust.cov.100.men.25.40.cov.75.sd, RMSE.error.infer.clust.cov.100.men.25.40.cov.80.sd,
RMSE.error.infer.clust.cov.100.men.25.40.cov.85.sd, RMSE.error.infer.clust.cov.100.men.25.40.cov.90.sd,
RMSE.error.infer.clust.cov.100.men.25.40.cov.95.sd))
plot.RMSE.error.infer.clust.cov.100.men.25.40.AD.sd <- ggplot(RMSE.error.infer.clust.cov.100.men.25.40.AD.sd, aes(x = x, y = F)) +
geom_point(size = 4) +
ggtitle("Error for SD age difference for men in 25 - 40 - MCAR") +
xlab("Sequence sampling coverage") + ylab("Error value")
# plot.RMSE.error.infer.clust.cov.100.men.25.40.AD.sd# 40 - 50
RMSE.error.infer.clust.cov.100.women.40.50.AD.mean <- data.frame(x=c("35", "40", "45",
"50", "55", "60",
"65", "70", "75",
"80", "85", "90",
"95"),
F = c(RMSE.error.infer.clust.cov.100.women.40.50.cov.35.mean, RMSE.error.infer.clust.cov.100.women.40.50.cov.40.mean,
RMSE.error.infer.clust.cov.100.women.40.50.cov.45.mean, RMSE.error.infer.clust.cov.100.women.40.50.cov.50.mean,
RMSE.error.infer.clust.cov.100.women.40.50.cov.55.mean, RMSE.error.infer.clust.cov.100.women.40.50.cov.60.mean,
RMSE.error.infer.clust.cov.100.women.40.50.cov.65.mean, RMSE.error.infer.clust.cov.100.women.40.50.cov.70.mean,
RMSE.error.infer.clust.cov.100.women.40.50.cov.75.mean, RMSE.error.infer.clust.cov.100.women.40.50.cov.80.mean,
RMSE.error.infer.clust.cov.100.women.40.50.cov.85.mean, RMSE.error.infer.clust.cov.100.women.40.50.cov.90.mean,
RMSE.error.infer.clust.cov.100.women.40.50.cov.95.mean))
plot.RMSE.error.infer.clust.cov.100.women.40.50.AD.mean <- ggplot(RMSE.error.infer.clust.cov.100.women.40.50.AD.mean, aes(x = x, y = F)) +
geom_point(size = 4) +
ggtitle("Error for mean age difference for women in 40 - 50 - MCAR") +
xlab("Sequence sampling coverage") + ylab("Error value")
# plot.RMSE.error.infer.clust.cov.100.women.40.50.AD.meanRMSE.error.infer.clust.cov.100.men.40.50.AD.mean <- data.frame(x=c("35", "40", "45",
"50", "55", "60",
"65", "70", "75",
"80", "85", "90",
"95"),
F = c(RMSE.error.infer.clust.cov.100.men.40.50.cov.35.mean, RMSE.error.infer.clust.cov.100.men.40.50.cov.40.mean,
RMSE.error.infer.clust.cov.100.men.40.50.cov.45.mean, RMSE.error.infer.clust.cov.100.men.40.50.cov.50.mean,
RMSE.error.infer.clust.cov.100.men.40.50.cov.55.mean, RMSE.error.infer.clust.cov.100.men.40.50.cov.60.mean,
RMSE.error.infer.clust.cov.100.men.40.50.cov.65.mean, RMSE.error.infer.clust.cov.100.men.40.50.cov.70.mean,
RMSE.error.infer.clust.cov.100.men.40.50.cov.75.mean, RMSE.error.infer.clust.cov.100.men.40.50.cov.80.mean,
RMSE.error.infer.clust.cov.100.men.40.50.cov.85.mean, RMSE.error.infer.clust.cov.100.men.40.50.cov.90.mean,
RMSE.error.infer.clust.cov.100.men.40.50.cov.95.mean))
plot.RMSE.error.infer.clust.cov.100.men.40.50.AD.mean <- ggplot(RMSE.error.infer.clust.cov.100.men.40.50.AD.mean, aes(x = x, y = F)) +
geom_point(size = 4) +
ggtitle("Error for mean age difference for men in 40 - 50 - MCAR") +
xlab("Sequence sampling coverage") + ylab("Error value")
# plot.RMSE.error.infer.clust.cov.100.men.40.50.AD.meanRMSE.error.infer.clust.cov.100.women.40.50.AD.med <- data.frame(x=c("35", "40", "45",
"50", "55", "60",
"65", "70", "75",
"80", "85", "90",
"95"),
F = c(RMSE.error.infer.clust.cov.100.women.40.50.cov.35.med, RMSE.error.infer.clust.cov.100.women.40.50.cov.40.med,
RMSE.error.infer.clust.cov.100.women.40.50.cov.45.med, RMSE.error.infer.clust.cov.100.women.40.50.cov.50.med,
RMSE.error.infer.clust.cov.100.women.40.50.cov.55.med, RMSE.error.infer.clust.cov.100.women.40.50.cov.60.med,
RMSE.error.infer.clust.cov.100.women.40.50.cov.65.med, RMSE.error.infer.clust.cov.100.women.40.50.cov.70.med,
RMSE.error.infer.clust.cov.100.women.40.50.cov.75.med, RMSE.error.infer.clust.cov.100.women.40.50.cov.80.med,
RMSE.error.infer.clust.cov.100.women.40.50.cov.85.med, RMSE.error.infer.clust.cov.100.women.40.50.cov.90.med,
RMSE.error.infer.clust.cov.100.women.40.50.cov.95.med))
plot.RMSE.error.infer.clust.cov.100.women.40.50.AD.med <- ggplot(RMSE.error.infer.clust.cov.100.women.40.50.AD.med, aes(x = x, y = F)) +
geom_point(size = 4) +
ggtitle("Error for median age difference for women in 40 - 50 - MCAR") +
xlab("Sequence sampling coverage") + ylab("Error value")
# plot.RMSE.error.infer.clust.cov.100.women.40.50.AD.medRMSE.error.infer.clust.cov.100.men.40.50.AD.med <- data.frame(x=c("35", "40", "45",
"50", "55", "60",
"65", "70", "75",
"80", "85", "90",
"95"),
F = c(RMSE.error.infer.clust.cov.100.men.40.50.cov.35.med, RMSE.error.infer.clust.cov.100.men.40.50.cov.40.med,
RMSE.error.infer.clust.cov.100.men.40.50.cov.45.med, RMSE.error.infer.clust.cov.100.men.40.50.cov.50.med,
RMSE.error.infer.clust.cov.100.men.40.50.cov.55.med, RMSE.error.infer.clust.cov.100.men.40.50.cov.60.med,
RMSE.error.infer.clust.cov.100.men.40.50.cov.65.med, RMSE.error.infer.clust.cov.100.men.40.50.cov.70.med,
RMSE.error.infer.clust.cov.100.men.40.50.cov.75.med, RMSE.error.infer.clust.cov.100.men.40.50.cov.80.med,
RMSE.error.infer.clust.cov.100.men.40.50.cov.85.med, RMSE.error.infer.clust.cov.100.men.40.50.cov.90.med,
RMSE.error.infer.clust.cov.100.men.40.50.cov.95.med))
plot.RMSE.error.infer.clust.cov.100.men.40.50.AD.med <- ggplot(RMSE.error.infer.clust.cov.100.men.40.50.AD.med, aes(x = x, y = F)) +
geom_point(size = 4) +
ggtitle("Error for median age difference for men in 40 - 50 - MCAR") +
xlab("Sequence sampling coverage") + ylab("Error value")
# plot.RMSE.error.infer.clust.cov.100.men.40.50.AD.medRMSE.error.infer.clust.cov.100.women.40.50.AD.sd <- data.frame(x=c("35", "40", "45",
"50", "55", "60",
"65", "70", "75",
"80", "85", "90",
"95"),
F = c(RMSE.error.infer.clust.cov.100.women.40.50.cov.35.sd, RMSE.error.infer.clust.cov.100.women.40.50.cov.40.sd,
RMSE.error.infer.clust.cov.100.women.40.50.cov.45.sd, RMSE.error.infer.clust.cov.100.women.40.50.cov.50.sd,
RMSE.error.infer.clust.cov.100.women.40.50.cov.55.sd, RMSE.error.infer.clust.cov.100.women.40.50.cov.60.sd,
RMSE.error.infer.clust.cov.100.women.40.50.cov.65.sd, RMSE.error.infer.clust.cov.100.women.40.50.cov.70.sd,
RMSE.error.infer.clust.cov.100.women.40.50.cov.75.sd, RMSE.error.infer.clust.cov.100.women.40.50.cov.80.sd,
RMSE.error.infer.clust.cov.100.women.40.50.cov.85.sd, RMSE.error.infer.clust.cov.100.women.40.50.cov.90.sd,
RMSE.error.infer.clust.cov.100.women.40.50.cov.95.sd))
plot.RMSE.error.infer.clust.cov.100.women.40.50.AD.sd <- ggplot(RMSE.error.infer.clust.cov.100.women.40.50.AD.sd, aes(x = x, y = F)) +
geom_point(size = 4) +
ggtitle("Error for SD age difference for women in 40 - 50 - MCAR") +
xlab("Sequence sampling coverage") + ylab("Error value")
# plot.RMSE.error.infer.clust.cov.100.women.40.50.AD.sdRMSE.error.infer.clust.cov.100.men.40.50.AD.sd <- data.frame(x=c("35", "40", "45",
"50", "55", "60",
"65", "70", "75",
"80", "85", "90",
"95"),
F = c(RMSE.error.infer.clust.cov.100.men.40.50.cov.35.sd, RMSE.error.infer.clust.cov.100.men.40.50.cov.40.sd,
RMSE.error.infer.clust.cov.100.men.40.50.cov.45.sd, RMSE.error.infer.clust.cov.100.men.40.50.cov.50.sd,
RMSE.error.infer.clust.cov.100.men.40.50.cov.55.sd, RMSE.error.infer.clust.cov.100.men.40.50.cov.60.sd,
RMSE.error.infer.clust.cov.100.men.40.50.cov.65.sd, RMSE.error.infer.clust.cov.100.men.40.50.cov.70.sd,
RMSE.error.infer.clust.cov.100.men.40.50.cov.75.sd, RMSE.error.infer.clust.cov.100.men.40.50.cov.80.sd,
RMSE.error.infer.clust.cov.100.men.40.50.cov.85.sd, RMSE.error.infer.clust.cov.100.men.40.50.cov.90.sd,
RMSE.error.infer.clust.cov.100.men.40.50.cov.95.sd))
plot.RMSE.error.infer.clust.cov.100.men.40.50.AD.sd <- ggplot(RMSE.error.infer.clust.cov.100.men.40.50.AD.sd, aes(x = x, y = F)) +
geom_point(size = 4) +
ggtitle("Error for SD age difference for men in 40 - 50 - MCAR") +
xlab("Sequence sampling coverage") + ylab("Error value")
# plot.RMSE.error.infer.clust.cov.100.men.40.50.AD.sd5.3.1 Goodness of fit of age difference statistics for critical age groups
df_gps_mean <- rbind(RMSE.error.infer.clust.cov.100.men.15.25.AD.mean,
RMSE.error.infer.clust.cov.100.men.25.40.AD.mean,
RMSE.error.infer.clust.cov.100.men.40.50.AD.mean,
RMSE.error.infer.clust.cov.100.women.15.25.AD.mean,
RMSE.error.infer.clust.cov.100.women.25.40.AD.mean,
RMSE.error.infer.clust.cov.100.women.40.50.AD.mean)
d_mean <- df_gps_mean
d_mean$param <- c(rep("Males.15.25", nrow(RMSE.error.infer.clust.cov.100.men.15.25.AD.mean)),
rep("Males.25.40", nrow(RMSE.error.infer.clust.cov.100.men.25.40.AD.mean)),
rep("Males.40.50", nrow(RMSE.error.infer.clust.cov.100.men.40.50.AD.mean)),
rep("Females.15.25", nrow(RMSE.error.infer.clust.cov.100.women.15.25.AD.mean)),
rep("Females.25.40", nrow(RMSE.error.infer.clust.cov.100.women.25.40.AD.mean)),
rep("Females.40.50", nrow(RMSE.error.infer.clust.cov.100.women.40.50.AD.mean)))
newdata_mean <- d_mean[order(d_mean$param),]
newdata_mean$f_m <- c(rep("Females", nrow(newdata_mean)/2), rep("Males", nrow(newdata_mean)/2))
newdata_mean$age_groups <- c(rep("15_25", nrow(RMSE.error.infer.clust.cov.100.men.15.25.AD.mean)),
rep("25_40", nrow(RMSE.error.infer.clust.cov.100.men.25.40.AD.mean)),
rep("40_50", nrow(RMSE.error.infer.clust.cov.100.men.40.50.AD.mean)),
rep("15_25", nrow(RMSE.error.infer.clust.cov.100.women.15.25.AD.mean)),
rep("25_40", nrow(RMSE.error.infer.clust.cov.100.women.25.40.AD.mean)),
rep("40_50", nrow(RMSE.error.infer.clust.cov.100.women.40.50.AD.mean)))
colnames(newdata_mean) <- c("cov", "val", "param", "f_m", "age_groups")
saveRDS(newdata_mean, file = "/home/david/age_mixing_patterns_phylogenetic/results/MAR_a/MAR_a_15_Error_for_Mean_Age_Difference.RDS")
plot.mean.AD_seq_cov_errors_100 <- ggplot(newdata_mean, aes(x=cov, y=val, colour= age_groups, group = age_groups)) +
geom_line(size=1) +
geom_point() +
facet_grid(. ~ f_m) +
# theme(legend.position="top")+
xlab("Sampling Coverage (%)") + ylab("Error value for mean of age difference")
print(plot.mean.AD_seq_cov_errors_100)
ggsave(filename = "Plot_a_15_Error_for_Mean_Age_Difference.pdf",
plot = plot.mean.AD_seq_cov_errors_100,
path = "/home/david/age_mixing_patterns_phylogenetic/results/MAR_a",
width = 26, height = 15, units = "cm")df_gps_sd <- rbind(RMSE.error.infer.clust.cov.100.men.15.25.AD.sd,
RMSE.error.infer.clust.cov.100.men.25.40.AD.sd,
RMSE.error.infer.clust.cov.100.men.40.50.AD.sd,
RMSE.error.infer.clust.cov.100.women.15.25.AD.sd,
RMSE.error.infer.clust.cov.100.women.25.40.AD.sd,
RMSE.error.infer.clust.cov.100.women.40.50.AD.sd)
d_sd <- df_gps_sd
d_sd$param <- c(rep("Males.15.25", nrow(RMSE.error.infer.clust.cov.100.men.15.25.AD.sd)),
rep("Males.25.40", nrow(RMSE.error.infer.clust.cov.100.men.25.40.AD.sd)),
rep("Males.40.50", nrow(RMSE.error.infer.clust.cov.100.men.40.50.AD.sd)),
rep("Females.15.25", nrow(RMSE.error.infer.clust.cov.100.women.15.25.AD.sd)),
rep("Females.25.40", nrow(RMSE.error.infer.clust.cov.100.women.25.40.AD.sd)),
rep("Females.40.50", nrow(RMSE.error.infer.clust.cov.100.women.40.50.AD.sd)))
newdata_sd <- d_sd[order(d_sd$param),]
newdata_sd$f_m <- c(rep("Females", nrow(newdata_sd)/2), rep("Males", nrow(newdata_sd)/2))
newdata_sd$age_groups <- c(rep("15_25", nrow(RMSE.error.infer.clust.cov.100.men.15.25.AD.sd)),
rep("25_40", nrow(RMSE.error.infer.clust.cov.100.men.25.40.AD.sd)),
rep("40_50", nrow(RMSE.error.infer.clust.cov.100.men.40.50.AD.sd)),
rep("15_25", nrow(RMSE.error.infer.clust.cov.100.women.15.25.AD.sd)),
rep("25_40", nrow(RMSE.error.infer.clust.cov.100.women.25.40.AD.sd)),
rep("40_50", nrow(RMSE.error.infer.clust.cov.100.women.40.50.AD.sd)))
colnames(newdata_sd) <- c("cov", "val", "param", "f_m", "age_groups")
saveRDS(newdata_sd, file = "/home/david/age_mixing_patterns_phylogenetic/results/MAR_a/MAR_a_16_Error_for_SD_Age_Difference.RDS")
plot.sd.AD_seq_cov_errors_100 <- ggplot(newdata_sd, aes(x=cov, y=val, colour= age_groups, group = age_groups)) +
geom_line(size=1)+
geom_point() +
facet_grid(. ~ f_m) +
# theme(legend.position="top")+
xlab("Sampling Coverage (%)") + ylab("Error value for SD of age difference")
print(plot.sd.AD_seq_cov_errors_100)
ggsave(filename = "Plot_a_16_Error_for_SD_Age_Difference.pdf",
plot = plot.sd.AD_seq_cov_errors_100,
path = "/home/david/age_mixing_patterns_phylogenetic/results/MAR_a",
width = 26, height = 15, units = "cm")
pdf("/home/david/age_mixing_patterns_phylogenetic/results/MAR_a/Plot_a_17_Error_Mean_SD_Age_Difference_at_35_95_Coverage.pdf",
width=15, height=15)
gridExtra::grid.arrange(plot.mean.AD_seq_cov_errors_100, plot.sd.AD_seq_cov_errors_100)
dev.off()## png
## 2pdf("/home/david/age_mixing_patterns_phylogenetic/results/MAR_a/Plot_a_11_15_Mean_Age_Difference_and_Error_at_35_95_Coverage.pdf",
width=15, height=15)
gridExtra::grid.arrange(plot.mean.men.women.AD.df, plot.mean.AD_seq_cov_errors_100)
dev.off()## png
## 2pdf("/home/david/age_mixing_patterns_phylogenetic/results/MAR_a/Plot_a_13_16_SD_Age_Difference_and_Error_at_35_95_Coverage.pdf",
width=15, height=15)
gridExtra::grid.arrange(plot.sd.men.women.AD.df, plot.sd.AD_seq_cov_errors_100)
dev.off()## png
## 2